Optical fiber sensing early-warning method and related device

Abstract

An optical fiber sensing early-warning method applicable to a network management system (304), and a related device, wherein the network management system (304) is in communication connection with one or more early-warning units (302), and each early-warning unit (302) corresponds to at least one sensing optical fiber (302). The method comprises: acquiring historical early-warning information of one or more early-warning units (302) (S401); acquiring current early-warning information of the one or more early-warning units (302) (S402), wherein the current early-warning information comprises one or more pieces of current event information; and on the basis of the historical early-warning information and the current early-warning information, determining M intrusion objects corresponding to the one or more pieces of current event information, and determining motion information of each of the M intrusion objects (S403), wherein each piece of motion information comprises a position change pattern of a corresponding intrusion object. In the method, when an intrusion object is in a moving state, by means of an optical fiber sensing system, a security personnel can be assisted in accurately and promptly tracking and addressing the intrusion object, so as to quickly eliminate a security risk.

Description

A fiber optic sensing early warning method and related equipment

[0001] This application claims priority to Chinese Patent Application No. 202410504272.9, filed on April 24, 2024, entitled "A Fiber Optic Sensing Early Warning Method and Related Equipment", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of security technology, and in particular to a fiber optic sensing early warning method and related equipment. Background Technology

[0003] Fiber optic sensing technology measures the backscattered signal in an optical fiber to obtain the fiber's (hereinafter referred to as the sensing fiber) response to external disturbances such as vibration, strain, and temperature changes, thereby enabling environmental monitoring. Distributed optical fiber acoustic sensing (DAS) systems employing fiber optic sensing technology possess high sensitivity, fast measurement response speed, and are suitable for long-distance, fully distributed sensing. Therefore, they are widely used in building structural health monitoring, perimeter security, and other fields. Specifically, distributed optical fiber acoustic sensing systems primarily rely on phase-sensitive optical time domain reflectometer (Φ-OTDR) technology to achieve continuous distributed sensing of weak disturbance events (also known as intrusion events) distributed along the sensing fiber, thereby accurately locating the specific position of the disturbance source (also known as the intrusion target). However, existing security mechanisms based on fiber optic sensing systems such as distributed fiber optic acoustic sensing systems (e.g., perimeter security mechanisms) typically only detect and alarm on intrusion events that have already occurred. They then notify security personnel (e.g., perimeter patrol personnel) to arrive at the scene of the intrusion to handle it. However, since it generally takes some time for security personnel to arrive at the scene, the location of the intrusion is often not the actual location of the intruder when the intruder arrives. As a result, security personnel cannot accurately and promptly track and handle the intruder based on the alarm information, and cannot quickly eliminate security risks.

[0004] Therefore, how to use fiber optic sensing systems to assist security personnel in accurately and promptly tracking and dealing with intruders when they are in motion, so as to quickly eliminate security risks, is an urgent problem to be solved. Summary of the Invention

[0005] To address the aforementioned technical problems, this application provides a fiber optic sensing early warning method and related equipment, which assists security personnel in accurately and promptly tracking and handling intrusion targets when they are in motion, thereby quickly eliminating security risks.

[0006] In a first aspect, embodiments of this application provide a fiber optic sensing early warning method. This method can be applied to a network management system, which can be communicatively connected to one or more early warning units, each of which corresponds to at least one sensing fiber. The fiber optic sensing early warning method may include:

[0007] The system acquires historical early warning information from the one or more early warning units. The historical early warning information includes one or more historical event information, each of which includes first description information of a processed intrusion event along the sensing fiber. The first description information includes the intrusion target, intrusion location, and intrusion time of the corresponding intrusion event. The system also acquires current early warning information from the one or more early warning units. The current early warning information includes one or more current event information, each of which includes second description information of an unprocessed intrusion event along the sensing fiber. The second description information includes the intrusion location and intrusion time of the corresponding intrusion event. Based on the historical early warning information and the current early warning information, the system determines M intrusion targets corresponding to the one or more current event information, and determines the motion information of each of the M intrusion targets. The motion information includes the position change pattern of the corresponding intrusion target, where M is an integer greater than 0.

[0008] This application provides a fiber optic sensing early warning method applied in a network management system. The network management system can communicate with one or more early warning units, each corresponding to at least one sensing fiber. The network management system, the one or more early warning units, and the sensing fibers corresponding to each early warning unit can form a fiber optic sensing system. In the prior art, when an intrusion event occurs (i.e., an intruder disturbs the sensing fiber), the network management system analyzes the early warning information sent by each early warning unit. The resulting analysis information is often only used to notify security personnel to arrive at the scene (i.e., the location of the intrusion event) for handling. If the intruder is moving, the security personnel... Personnel are unable to accurately and promptly track and handle the intrusion target based on the analysis information, and cannot quickly eliminate security risks. Compared with the prior art, the fiber optic sensing early warning method provided in this application embodiment can obtain historical early warning information of each early warning unit, that is, obtain one or more historical event information sent by each early warning unit that has been processed by the network management system; and obtain current early warning information of each early warning unit, that is, obtain one or more current event information sent by each early warning unit that is waiting to be processed by the network management system; and then combine the historical early warning information and the current early warning information for analysis to obtain analysis information containing the location change pattern (e.g., trajectory, speed, etc.) of the corresponding intrusion target. Specifically, when processing event information, the network management system can combine feedback from security personnel regarding the handling of corresponding intrusion events to identify and add the intrusion target to the event information. Therefore, in addition to the intrusion location and time of the intrusion event, the historical warning information can also include the intrusion target. In this case, the historical warning information can include examples of the correspondence between intrusion targets and intrusion events, and how the location of the intrusion target changes. Taking the correspondence between intrusion targets and intrusion events as an example, the examples of this correspondence can be used to analyze the conditions satisfied by the intrusion location and intrusion time of multiple intrusion events corresponding to the same intrusion target. Therefore, by combining the historical warning information, one or more intrusion targets corresponding to the current warning information can be identified through analysis. Each intrusion target corresponds to one or more intrusion events to be handled. Then, the possible location change patterns of each intrusion target can be analyzed and predicted. Thus, when the intrusion target is in a moving state, this embodiment of the application can use the analysis information containing the location change patterns of the corresponding intrusion target to assist security personnel in accurately and timely tracking and handling the corresponding intrusion target, so as to quickly eliminate security risks.

[0009] In one possible implementation, determining the M intrusion objects corresponding to the one or more current event information based on the historical warning information and the current warning information includes: dividing the one or more current event information into one or more groups based on the historical warning information and the current warning information, each group including at least one current event information, and each intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; and determining the M intrusion objects based on the one or more groups. This application provides a specific implementation scheme for determining M intrusion objects based on historical and current warning information. The M intrusion objects can correspond to one or more current event information in the current warning information. Specifically, each of the M intrusion objects can correspond to at least one intrusion event to be processed, that is, to at least one current event information. Therefore, when there are instances of correspondence between intrusion objects and intrusion events in the historical warning information, the instances can be analyzed to divide the one or more current event information into one or more groups, and determine which current event information corresponds to the same intrusion object. This not only accurately defines the correspondence between current event information and intrusion objects, but also uses the correspondence to define and distinguish the M intrusion objects. The scheme is simple and fast.

[0010] In one possible implementation, the first description information further includes the movement trajectory of the intrusion object corresponding to the intrusion event; determining the movement information of each of the M intrusion objects includes: determining the movement trajectories of N intrusion objects among the M intrusion objects based on the historical warning information and the current warning information, where N is an integer greater than 0 and less than or equal to M. This application provides a specific implementation scheme for determining the positional change pattern of intrusion objects based on historical warning information and current warning information. Since the movement route of the corresponding intrusion object after the intrusion event is often recorded when processing an intrusion event, the first description information of the processed intrusion event obtained by the network management system may also include the movement trajectory of the corresponding intrusion object. That is, the historical warning information may include some instances of the movement trajectory of the intrusion object. Therefore, the historical warning information can be combined with the current warning information, and by analyzing some instances of the movement trajectory of the intrusion object in the historical warning information, the movement trajectories of all or part of the M intrusion objects (e.g., N intrusion objects) corresponding to the current warning information can be predicted. This scheme is simple and fast, and helps to improve the accuracy of movement trajectory prediction.

[0011] In one possible implementation, determining the movement trajectories of N intrusion objects out of the M intrusion objects based on the historical warning information and the current warning information includes: determining at least one historical event information that satisfies a first condition based on the historical warning information and the current warning information, and determining the current event information corresponding to each of the N intrusion objects; determining the movement trajectory of each of the N intrusion objects based on the at least one historical event information that satisfies the first condition and based on the current event information corresponding to each of the N intrusion objects. This application provides a specific implementation scheme for determining the movement trajectories of N intrusion objects based on historical and current warning information. When the first description information of the processed intrusion event obtained by the network management system includes the movement trajectory of the corresponding intrusion object, that is, when the historical warning information includes some instances of the movement trajectory of the intrusion object, one or more historical event information in the historical warning information can be filtered through preset judgment conditions (i.e., the first condition) to determine which first description information in the historical event information can be used for analysis, that is, to filter out the historical event information related to the N intrusion objects in the historical warning information. Then, by analyzing the instances of the correspondence between intrusion objects and intrusion events in the historical warning information, it can be determined which current event information in the current warning information corresponds to the same intrusion object, that is, to determine at least one current event information corresponding to each of the N intrusion objects. Thus, the movement trajectory of each of the N intrusion objects can be predicted by using the historical event information related to the N intrusion objects in the historical warning information and the at least one current event information corresponding to each of the N intrusion objects. The scheme is simple and fast, and is conducive to improving the accuracy of movement trajectory prediction.

[0012] In one possible implementation, the first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects. This application provides a specific solution for the first condition, which is a preset judgment condition for filtering one or more historical event information in historical warning information. Since intrusion objects with the same or similar intrusion locations are highly likely to have the same or similar movement trajectories, the first condition can be set as: the distance between the corresponding intrusion event and the intrusion location of at least one intrusion event to be processed is less than or equal to a preset distance, and the intrusion event to be processed is an intrusion event corresponding to N intrusion objects. At this time, the intrusion location of a processed intrusion event corresponding to the historical event information that satisfies the first condition is at least within a preset range (i.e., less than or equal to a preset distance) of the intrusion location of an intrusion event to be processed. Therefore, the first descriptive information in the historical event information that satisfies the first condition can be used for analysis, meaning that the historical event information that satisfies the first condition is related to the N intrusion objects. This solution is simple and quick.

[0013] In one possible implementation, the first description information and the second description information further include the type of the intrusion object corresponding to the corresponding intrusion event, and the historical event information that satisfies the first condition also satisfies the second condition, which is: the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects. This application provides a specific solution for the second condition, which is another preset judgment condition for filtering one or more historical event information in historical early warning information, in addition to the first condition. Since different types of intrusion objects usually cause different disturbances to the sensing optical fiber, when the early warning unit processes the optical signal in the sensing optical fiber after an intrusion event occurs, it can also identify the type of intrusion object (e.g., personnel or vehicles) corresponding to the intrusion event. Therefore, the event information (i.e., the first description information and the second description information) obtained by the early warning unit can also include the type of intrusion object. In addition, since intrusion objects of the same type are more likely to have the same or similar movement trajectories, the second condition can be set as follows: the corresponding intrusion event corresponds to the same type of intrusion object as at least one intrusion event to be processed, and the intrusion event to be processed is an intrusion event corresponding to N intrusion objects. At this time, it can be considered that the first description information in the historical event information that simultaneously satisfies the first condition and the second condition can be used for analysis, that is, it is considered that the historical event information that simultaneously satisfies the first condition and the second condition is related to the N intrusion objects. The solution is simple and fast. It should be noted that the type of intrusion object can correspond to the type of intrusion event. For example, when the types of intrusion events are excavator intrusion and personnel intrusion, the corresponding types of intrusion objects are excavator and personnel, respectively.

[0014] In one possible implementation, determining the movement information of each of the M intrusion objects further includes: determining the position of each of the N intrusion objects at one or more times based on the movement trajectories of the N intrusion objects. This application provides a specific implementation scheme for determining the position change pattern of intrusion objects based on historical and current warning information. After determining the movement trajectories of the N intrusion objects out of the M intrusion objects, the position of each of the N intrusion objects at one or more times can be determined based on the movement trajectories. The position at one or more times can be recorded in the form of time-location pairs, for example, ((time 1, position 1), (time 2, position 2), ...). In this case, if the position at one or more times is used as the position change pattern of the intrusion object, a notification message containing this position change pattern is sent to security personnel, enabling them to track and handle the intrusion object according to the position change pattern. This simplifies the process of sending the notification message, makes the message more concise and clear, reduces the difficulty for security personnel to understand the message, and speeds up the elimination of security risks.

[0015] In one possible implementation, after determining the movement information of each of the M intrusion objects, the method further includes: sending a first request to a geographic information system based on the movement trajectory of each of the N intrusion objects, wherein the geographic information system is communicatively connected to the network management system; receiving a response from the geographic information system to the first request, and generating a trajectory map of each of the N intrusion objects based on the response, wherein the trajectory map includes corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object. This application provides a specific implementation scheme for generating a corresponding trajectory map based on the movement trajectory of an intrusion object. After determining the position change pattern, i.e., the movement trajectory, of N intrusion objects, the trajectory map of the N intrusion objects can be generated through communication between the network management system and the geographic information system (i.e., sending requests and receiving responses). Since the trajectory map includes corresponding map information (e.g., display of locations and roads) and a graphical representation of the movement trajectory (e.g., straight lines, polylines, or curves representing the movement trajectory), it is more intuitive and comprehensive. If a notification message containing the trajectory map is sent to security personnel, enabling them to track and deal with the intrusion objects according to the trajectory map, it will help speed up the elimination of security risks.

[0016] In one possible implementation, determining the movement information of each of the M intrusion objects includes: determining the movement speed and direction of L intrusion objects among the M intrusion objects based on the historical warning information and the current warning information, where L is an integer greater than 0 and less than or equal to M. This application provides a specific implementation scheme for determining the position change pattern of intrusion objects based on historical warning information and current warning information. On the one hand, when processing an intrusion event, the movement route of the corresponding intrusion object after the intrusion event is often recorded. At this time, the first description information of the processed intrusion event obtained by the network management system may also include the movement speed and direction of the corresponding intrusion object at one or more times. That is, the historical warning information may include some instances of the movement speed and direction of the intrusion object. Therefore, the historical warning information can be combined with the current warning information, and by analyzing some instances of the movement speed and direction of the intrusion object in the historical warning information, the movement speed and direction of all or part of the M intrusion objects (e.g., L intrusion objects) corresponding to the current warning information can be predicted. On the other hand, even if the first description information does not include the movement speed and direction of the corresponding intrusion object... If the historical warning information includes instances of the correspondence between intrusion objects and intrusion events, it can be combined with the current warning information. By analyzing the instances of the correspondence between intrusion objects and intrusion events in the historical warning information, it can be determined which current event information in the current warning information corresponds to the same intrusion object. Thus, if each of the L intrusion objects out of the M intrusion objects corresponds to at least two current event information (that is, at least two intrusion events to be processed), then at least one possible speed and direction of movement for each of the L intrusion objects can be obtained from the intrusion location and intrusion time in the at least two current event information. Based on the above, the speed and direction of movement of intrusion objects can be determined based on historical warning information and current warning information. This method is simple and fast, and also helps to improve the accuracy of speed and direction of movement prediction.

[0017] In one possible implementation, the first description information further includes the movement speed and direction of the intrusion object corresponding to the intrusion event; determining the movement speed and direction of L intrusion objects out of the M intrusion objects based on the historical event information and the warning information includes: determining at least one historical event information that satisfies a third condition based on the historical warning information and the current warning information, and determining the current event information corresponding to each of the L intrusion objects; determining the movement speed and direction of each of the L intrusion objects at one or more times based on the at least one historical event information that satisfies the third condition and based on the current event information corresponding to each of the L intrusion objects. This application provides a specific implementation scheme for determining the movement speed and direction of L intrusion objects based on historical and current early warning information. When the first description information of the processed intrusion event obtained by the network management system includes the movement speed and direction of the corresponding intrusion object, that is, when the historical early warning information includes some instances of the movement speed and direction of the intrusion object, one or more historical event information in the historical early warning information can be filtered through preset judgment conditions (i.e., the third condition) to determine which historical event information's first description information can be used for analysis, that is, to filter out the historical events in the historical early warning information related to the L intrusion objects. Information; subsequently, by analyzing instances of the correspondence between intrusion objects and intrusion events in the historical early warning information, it can be determined which current event information in the current early warning information corresponds to the same intrusion object, that is, to determine at least one current event information corresponding to each of the L intrusion objects; thus, by using the historical event information related to the L intrusion objects in the historical early warning information, and the at least one current event information corresponding to each of the L intrusion objects, the movement speed and movement direction of each of the L intrusion objects can be predicted. The solution is simple and fast, and is conducive to improving the accuracy of movement speed and movement direction prediction.

[0018] In one possible implementation, the second descriptive information further includes the movement speed and direction of the intrusion object corresponding to the intrusion event. This application provides a specific composition of the second descriptive information. When an intrusion event occurs, i.e., an intrusion object disturbs the sensing fiber, a corresponding early warning unit can process the relevant information transmitted by the sensing fiber. The second descriptive information obtained after processing by the early warning unit can include not only the intrusion location and time of the intrusion event, but also the movement speed and direction of the intrusion object. For example, if the early warning unit determines that two intrusion events correspond to the same intrusion object, the early warning unit can determine the possible movement speed and direction of the intrusion object through the intrusion location and time of the two intrusion events. Then, if the early warning unit sends the current event information containing the second descriptive information to the network management system for analysis, it helps the network management system quickly generate analytical information containing the location change patterns of the intrusion object, which is beneficial for quickly eliminating security risks.

[0019] In one possible implementation, the position change pattern is the movement trajectory of the corresponding intrusion object and / or the movement speed and direction of the corresponding intrusion object; after determining the movement information of each intrusion object among the M intrusion objects, the method further includes: based on the historical warning information and the current warning information, determining the probability of occurrence of one or more of the position change patterns of each intrusion object among the K intrusion objects, wherein the K intrusion objects are the intrusion objects among the M intrusion objects, and K is an integer greater than 0 and less than or equal to M. This application provides a specific composition of the motion information of an intrusion object and a specific way of using such motion information. Among the M intrusion objects corresponding to the current warning information, the position change pattern in the motion information of each intrusion object can be the motion trajectory and / or the motion speed and direction of each intrusion object. At this time, the historical warning information can include some instances of the motion trajectory of the intrusion object, and / or some instances of the motion speed and direction of the intrusion object. Therefore, the historical warning information can be combined with the current warning information. By analyzing some instances of the motion trajectory and / or the motion speed and direction of the intrusion object in the historical warning information, the probability of one or more of the position change patterns occurring in all or some of the M intrusion objects (e.g., K intrusion objects) can be predicted. The solution is simple and fast. For example, if analysis shows that, in the historical warning information, among the intrusion events where the intrusion location is in area 3, 90% of the intruders will move to area 4 and 10% will move to area 5, then for the intrusion events where the intrusion location is in area 3, the probability that the intruder's trajectory is from area 3 to area 4 can be predicted as 90%, and the probability that it is from area 3 to area 5 can be predicted as 10%. Furthermore, sending notification messages containing one or more location change patterns and their corresponding probabilities to security personnel helps them to track and handle intruders more accurately and comprehensively.

[0020] Secondly, embodiments of this application provide a network management device, which can be communicatively connected to one or more early warning units, each early warning unit corresponding to at least one sensing optical fiber; the network management device may include:

[0021] The first information acquisition module is used to acquire historical early warning information of the one or more early warning units. The historical early warning information includes one or more historical event information. Each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description information includes the intrusion object, intrusion location and intrusion time of the corresponding intrusion event.

[0022] The second information acquisition module is used to acquire the current warning information of the one or more warning units. The current warning information includes one or more current event information. Each current event information includes a second description of an intrusion event to be processed by one of the sensing optical fibers. The second description information includes the intrusion location and intrusion time of the corresponding intrusion event.

[0023] The information processing module is used to determine M intrusion objects corresponding to the one or more current event information based on the historical early warning information and the current early warning information, and to determine the motion information of each of the M intrusion objects, wherein the motion information includes the position change pattern of the corresponding intrusion object, and M is an integer greater than 0.

[0024] In one possible implementation, the information processing module is specifically used to: divide the one or more current event information into one or more groups based on the historical warning information and the current warning information, each group including at least one current event information, and the intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; and determine the M intrusion objects based on the one or more groups.

[0025] In one possible implementation, the first description information further includes the movement trajectory of the intrusion object corresponding to the intrusion event; the information processing module is specifically used to: determine the movement trajectories of N intrusion objects out of the M intrusion objects based on the historical warning information and the current warning information, where N is an integer greater than 0 and less than or equal to M.

[0026] In one possible implementation, the information processing module is specifically configured to: determine at least one historical event information that satisfies a first condition based on the historical warning information and the current warning information, and determine the current event information corresponding to each of the N intrusion objects; and determine the movement trajectory of each of the N intrusion objects based on the at least one historical event information that satisfies the first condition and the current event information corresponding to each of the N intrusion objects.

[0027] In one possible implementation, the first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0028] In one possible implementation, the first description information and the second description information further include the type of the intrusion object corresponding to the corresponding intrusion event, and the historical event information that satisfies the first condition also satisfies the second condition, which is: the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0029] In one possible implementation, the information processing module is further configured to: determine the position of each of the N intrusion objects at one or more moments based on the movement trajectories of the N intrusion objects.

[0030] In one possible implementation, the network management device further includes: a graphical module, configured to send a first request to a geographic information system based on the movement trajectory of each of the N intrusion objects, wherein the geographic information system is communicatively connected to the network management system; receive a response from the geographic information system to the first request, and generate a trajectory map of each of the N intrusion objects based on the response, wherein the trajectory map includes corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object.

[0031] In one possible implementation, the information processing module is specifically used to: determine the movement speed and direction of movement of L intrusion objects out of the M intrusion objects based on the historical warning information and the current warning information, where L is an integer greater than 0 and less than or equal to M.

[0032] In one possible implementation, the first description information further includes the movement speed and direction of the intrusion object corresponding to the intrusion event; the information processing module is specifically used to: determine at least one historical event information that satisfies the third condition based on the historical warning information and the current warning information, and determine the current event information corresponding to each of the L intrusion objects; based on the at least one historical event information that satisfies the third condition, and based on the current event information corresponding to each of the L intrusion objects, determine the movement speed and direction of each of the L intrusion objects at one or more times.

[0033] In one possible implementation, the second description information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event.

[0034] In one possible implementation, the location change pattern is the movement trajectory of the corresponding intrusion object and / or the movement speed and direction of the corresponding intrusion object; the network management device further includes: a probability calculation module, used to determine the probability of occurrence of one or more of the location change patterns of each of the K intrusion objects based on the historical warning information and the current warning information, wherein the K intrusion objects are the intrusion objects among the M intrusion objects, and K is an integer greater than 0 and less than or equal to M.

[0035] Thirdly, embodiments of this application provide an electronic device including a processor and an interface circuit. The processor is used to communicate with other devices through the interface circuit, enabling the electronic device to execute the fiber optic sensing early warning method in any possible implementation of the first aspect described above.

[0036] Fourthly, embodiments of this application provide a computer program product, which includes computer program code, and when the computer program product is run on a computer, causes the computer to execute the fiber optic sensing early warning method in any possible implementation of the first aspect described above.

[0037] Fifthly, embodiments of this application provide a computer-readable storage medium including computer instructions that, when executed on a computing device, cause the computing device to perform the fiber optic sensing early warning method provided in any possible implementation of the first aspect.

[0038] Understandably, the network management device provided in the second aspect, the electronic device provided in the third aspect, the computer program product provided in the fourth aspect, and the computer-readable storage medium provided in the fifth aspect are all used to execute the fiber optic sensing early warning method provided in any possible implementation of the first aspect of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here. Attached Figure Description

[0039] The accompanying drawings are provided to more clearly illustrate the technical solutions of the embodiments of this application. The drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1A is a schematic diagram illustrating the working principle of an existing fiber optic sensing security technology provided in an embodiment of this application.

[0041] Figure 1B is a schematic diagram of the working principle of another existing fiber optic sensing security technology provided in the embodiment of this application;

[0042] Figure 1C is a schematic diagram illustrating the working principle of another existing fiber optic sensing security technology provided in the embodiments of this application.

[0043] Figure 2 is a schematic diagram of an application scenario provided by an embodiment of this application;

[0044] Figure 3 is a schematic diagram of the system architecture of a fiber optic sensing security system provided in an embodiment of this application;

[0045] Figure 4 is a flowchart illustrating an optical fiber sensing early warning method provided in an embodiment of this application;

[0046] Figure 5 is a flowchart illustrating another fiber optic sensing early warning method provided in an embodiment of this application;

[0047] Figure 6 is a flowchart illustrating another fiber optic sensing early warning method provided in an embodiment of this application;

[0048] Figure 7 is a flowchart illustrating another fiber optic sensing early warning method provided in an embodiment of this application;

[0049] Figure 8 is a flowchart illustrating another fiber optic sensing early warning method provided in an embodiment of this application;

[0050] Figure 9 is a schematic diagram of the structure of a network management device provided in an embodiment of this application;

[0051] Figure 10 is a schematic diagram of another network management device provided in an embodiment of this application. Detailed Implementation

[0052] The embodiments of this application will now be described with reference to the accompanying drawings.

[0053] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0054] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0055] The terms “component,” “module,” “system,” etc., used in this specification are used to refer to computer-related entities, hardware, firmware, combinations of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. As illustrated, applications running on computing devices and computing devices can both be components. One or more components may reside in a process and / or an execution thread, and components may be located on a single computer and / or distributed among two or more computers. Furthermore, these components can be executed from various computer-readable media on which various data structures are stored. Components can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system, and / or a network, such as the Internet interacting with other systems via signals).

[0056] First, this application analyzes and proposes the specific technical problem it aims to solve. When an intrusion event occurs, i.e., when an intruder disturbs the sensing fiber optic cable, how can a fiber optic sensing system assist security personnel in handling the intrusion event to eliminate security risks? In existing technologies, the main solutions include the following:

[0057] Option 1: A perimeter security mechanism based on a distributed fiber optic acoustic sensing system, which may include steps 1 to 4 below.

[0058] Step 1: The sensing fiber optic cable detects intrusion events. When an intruder, such as a person or vehicle, disturbs the sensing fiber optic cable (i.e., an intrusion event occurs), the optical signal in the sensing fiber optic cable will change accordingly, thus forming a perception of the intrusion event. For example, please refer to Figure 1A. Figure 1A is a schematic diagram of the working principle of a conventional fiber optic sensing security technology provided in an embodiment of this application. Fiber optic sensing security technology can be understood as a security mechanism based on a fiber optic sensing system, such as a perimeter security mechanism. In the sensing fiber shown in Figure 1A ①, there can be a forward pulse light as shown in Figure 1A ②. Since the refractive index of the fiber core generally fluctuates, when the forward pulse light propagates in the sensing fiber, the region in the fiber with the refractive index fluctuation will generate a Rayleigh backscattering (RBS) signal, that is, generate backscattered light as shown in Figure 1A ③. The backscattered light is opposite to the propagation direction of the forward pulse light. When an external disturbance event, such as a physical disturbance like sound wave or strain, occurs as shown in Figure 1A ④, the physical parameters of the backscattered light will change accordingly, enabling the sensing fiber to sense the external disturbance event.

[0059] Step 2: The early warning unit receives and processes the optical signal in the sensing fiber to generate corresponding sensing information, and then sends the sensing information to the server. For example, as shown in Figure 1A, the early warning unit can receive and process the backscattered light shown in Figure 1A (③) through the distributed optical fiber sensor demodulator shown in Figure 1A (⑤) to generate corresponding sensing information, such as generating a photocurrent signal corresponding to the backscattered light.

[0060] Step 3: The server receives the sensor information sent by the early warning unit, processes the sensor information to obtain the event information corresponding to the intrusion event, and then transmits the event information back to the early warning unit.

[0061] Step 4: The early warning unit receives the event information and sends it as an early warning message to the network management system (also known as the early warning management system). For example, please refer to Figure 1B. Figure 1B is a schematic diagram of the working principle of another existing fiber optic sensing security technology provided in this application embodiment. As shown in Figure 1B (1), the early warning message can usually include the fiber name, risk point distance, event occurrence time, and actual intrusion type. As shown in Figure 1B (2), the fiber name, such as "Fiber 1", is generally the name or number of the sensing fiber that caused the intrusion event; the risk point distance, such as "10000", is in meters and is generally the distance from the intrusion location to the reference point in the sensing fiber. Taking the optical distribution frame (ODF) as an example, the risk point distance can be the length of the sensing fiber between the intrusion location and the optical distribution frame; the event occurrence time, such as "2021-06-30 16:51:36", is generally the time of occurrence of the intrusion event, i.e., the intrusion time; the actual intrusion type, such as "excavator intrusion", is generally the type of intrusion event and corresponds to the type of intrusion object.

[0062] Step 5: The network management system receives the warning information and processes it. This typically includes calling the video surveillance system to capture images of the intrusion location and notifying security personnel to go to the intrusion location for handling via SMS or email. For example, please refer to Figure 1C. Figure 1C is a schematic diagram of the working principle of another existing fiber optic sensing security technology provided in this application embodiment. As shown in Figure 1C (1), the network management system can send an SMS to the user group "jihua-text" where the security personnel are located to notify the security personnel to go to the intrusion location for handling. The content of the SMS can be as shown in Figure 1C (2), including the fault type "intrusion threat", the type of intrusion event such as "manual excavation intrusion", the intrusion location such as "fiber optic distance: 17774.0m", and may also include other expressions of the intrusion location such as latitude and longitude "geographical location: 116.3834780, 36.5171610", the corresponding routing device "192.168.2.88B82" and the relative distance between the intrusion location and the routing device "+54.0m", etc.

[0063] The main drawback of this scheme is that after an intrusion event occurs, the early warning unit sends corresponding early warning information to the network management system. The network management system can usually only use this early warning information to alert the intrusion event, that is, to notify security personnel, such as perimeter patrol personnel, to rush to the intrusion location and handle the intrusion event on-site. When the intrusion target is in a moving state, since it generally takes some time for security personnel to arrive at the scene, by the time the security personnel arrive, the intrusion target is often far away from the scene, or even beyond the security personnel's line of sight. Even if the security personnel arrive at the intrusion location, they cannot track, intercept or otherwise handle the intrusion target, and cannot quickly and effectively eliminate the security risk.

[0064] Taking into account the shortcomings of existing technologies, the technical problems that this application actually aims to solve include: how to use a fiber optic sensing system to assist security personnel in accurately and promptly tracking and dealing with intrusion targets when they are in motion, so as to quickly eliminate security risks.

[0065] To facilitate understanding of the embodiments of this application, the following exemplary examples illustrate the scenarios in which the fiber optic sensing early warning method of this application is applied, which may include:

[0066] Scenario 1: Perimeter security scenario based on fiber optic sensing system. Perimeter security is mainly used for perimeter intrusion monitoring of various important facilities and key areas. Generally, sensing fiber optic cables are deployed at the perimeter (boundary area) of important facilities and key areas to sense and monitor related intrusion events. Specifically, please refer to Figure 2, which is a schematic diagram of an application scenario provided by an embodiment of this application. As shown in Figure 2, if area A is an external area and area B is a security area, sensing fiber optic cables can be deployed at the boundary between area A and area B to sense and monitor intrusion events related to area B. Among them, the sensing fiber optic cable between positions 1 and 2 in Figure 2 can correspond to early warning unit 1, and the sensing fiber optic cable between positions 2 and 3 in Figure 2 can correspond to early warning unit 2. At this time, if an intruder moves from area A to area B, the sensing fiber optic cable will detect intrusion events. If an optical fiber disturbance causes an intrusion event in the sensing fiber between location 1 and location 2, the sensing fiber between location 1 and location 2 can transmit relevant information about the intrusion event (such as the intrusion location) to early warning unit 1. Early warning unit 1 then processes this information to obtain event information, which can then be sent to the network management system for analysis. This analysis information can include the possible location change patterns of the intruder, such as possible movement trajectories, possible locations at one or more times, possible movement speeds, and movement directions. Thus, even if the intruder is in a moving state, security personnel can use this analysis information to accurately and promptly track and deal with the intruder, quickly eliminating security risks.

[0067] It is understood that the above application scenarios are only one exemplary implementation method in the embodiments of this application, and the application scenarios in the embodiments of this application include, but are not limited to, the above application scenarios.

[0068] Based on the aforementioned technical problems and the corresponding application scenarios in this application, and to facilitate understanding of the embodiments of this application, one system architecture on which the embodiments of this application are based will be described below. Please refer to Figure 3, which is a schematic diagram of the system architecture of a fiber optic sensing security system provided in an embodiment of this application. As shown in Figure 3, a fiber optic sensing security system based on fiber optic sensing technology typically includes a sensing fiber 301, an early warning unit 302, and a network management system 304. Optionally, it may also include a server 303 and a third-party system 305. There may be one or more sensing fibers 301, early warning units 302, and servers 303. The sensing fiber 301 can be communicatively connected to the corresponding early warning unit 302, and one early warning unit 302 can correspond to at least one sensing fiber 301. The early warning unit 302 can be communicatively connected to the corresponding server 303, and one server 303 can correspond to at least one early warning unit 302. Each early warning unit 302 can be communicatively connected to the network management system 304, and the network management system 304 can also be communicatively connected to the third-party system 305.

[0069] Specifically, the sensing fiber optic cable 301 is mainly used for sensing the raw signals of fiber optic sensing, and can generally be laid in various ways such as fiber optic network or fiber optic burial. For example, the sensing fiber optic cable 301 can be laid on the protective net shown in Figure 3, that is, using the fiber optic network laying method. This protective net can usually be set at the boundary of the security area. When an intrusion event to be handled occurs, for example, if an intruder A as shown in Figure 3 climbs, bumps, or touches the protective net, it will cause a disturbance to the sensing fiber optic cable 301 on the protective net. The sensing fiber optic cable 301 can transmit relevant information, such as the location of the disturbance (i.e., the intrusion location), to the corresponding early warning unit 302 through the optical signal in the fiber.

[0070] The early warning unit 302 is mainly used to send and receive monitoring signals, including receiving the optical signal in the corresponding sensing fiber 301, processing the relevant information carried in the optical signal to obtain one or more current event information, and then sending the one or more current event information to the network management system 304, etc. Each current event information corresponds to an intrusion event to be processed. For example, as shown in Figure 3, if the intrusion object A causes disturbance to the sensing fiber 301 at position ① and position ② at time T1 and time T2 respectively, that is, two different intrusion events occur on the sensing fiber 301 at position ① and the sensing fiber 301 at position ② respectively, then the two early warning units 302 corresponding to the two sensing fibers 301 at positions ① and ② will obtain two different current event information respectively, and send the two different current event information to the network management system 304 respectively.

[0071] For example, if the warning unit 302 determines that at least two pending intrusion events correspond to the same intrusion object, the warning unit 302 can determine the movement speed and movement direction of the intrusion object by the intrusion location and intrusion time of the at least two pending intrusion events.

[0072] For example, the early warning unit 302 can receive the optical signal in the corresponding sensing fiber 301 and generate corresponding sensing information, then send the sensing information to the corresponding server 303, and then receive the response from the server 303 to the sensing information, thereby processing the relevant information carried by the optical signal in the sensing fiber 301. The sensing information may include the phase information of the optical signal corresponding to one or more intrusion events to be processed, and the response may include one or more current event information. Specifically, when an intrusion event to be processed occurs, the phase of the optical signal in the sensing fiber 301 will change. The early warning unit 302 can generate corresponding sensing information from the phase change of the optical signal in the sensing fiber 301. For example, the early warning unit 302 can generate current signals of different intensities and convert the current signals into digital signals as sensing information, wherein the intensity of the current signal can change with the phase change of the optical signal in the sensing fiber 301.

[0073] Server 303, also known as host computer, is mainly used to receive sensor information sent by the corresponding early warning unit 302, process the sensor information to obtain one or more current event information, and then send the one or more current event information to the early warning unit 302.

[0074] For example, when the server processes the sensor information, it can first obtain the intrusion location and intrusion time of at least two intrusion events corresponding to the same intrusion object, and then determine the movement speed and movement direction of the corresponding intrusion object based on the intrusion location and intrusion time of the at least two intrusion events.

[0075] The network management system 304 is mainly used to acquire one or more historical event information (i.e., historical early warning information) and one or more current event information (i.e., current early warning information) sent by one or more early warning units 302. Then, it combines the one or more historical event information and the one or more current event information for analysis to obtain analysis information containing the location change pattern (e.g., trajectory, speed, etc.) of the corresponding intrusion object. Each historical event information corresponds to a processed intrusion event.

[0076] The third-party system 305 is mainly used to receive information and instructions sent by the network management system 304, so that the network management system 304 can handle intrusion events. For example, the third-party system 305 may include a geographic information system (GIS), a video surveillance system, a line patrol system, etc. The geographic information system can be used to assist the network management system 304 in locating and graphically displaying the location of intrusion events and intrusion targets; the video surveillance system can be used to assist the network management system 304 in calling the video surveillance device 306 shown in Figure 3 to capture images of the intrusion location and transmit them back; the line patrol system can be used to assist the network management system 304 in dispatching security personnel via SMS, email, etc., that is, notifying security personnel to go to the location of the intrusion or the location of the intrusion target to take appropriate action.

[0077] It is understood that the system architecture of the fiber optic sensing security technology described in Figure 3 above is only an exemplary implementation in the embodiments of this application. The system architecture of the fiber optic sensing security technology in the embodiments of this application includes, but is not limited to, the above system architecture.

[0078] Based on the system architecture shown in Figure 3 and the corresponding application scenario in this application, and combined with the fiber optic sensing early warning method provided in this application, the technical problems raised in this application are specifically analyzed and solved.

[0079] Please refer to Figure 4, which is a flowchart illustrating a fiber optic sensing early warning method provided in an embodiment of this application. This method can be applied to the system architecture described in Figure 3 above. The network management system 304 can support and execute steps S401-S404 of the method flow shown in Figure 4, and the network management system 304 can be communicatively connected to one or more early warning units 302, each corresponding to at least one sensing fiber optic cable 301. The following description, in conjunction with Figure 4, focuses on the network management system. Specifically, the method may include steps S401-S403, and optionally step S404.

[0080] Step S401: Obtain historical early warning information from the one or more early warning units.

[0081] Specifically, the historical early warning information includes one or more historical event information. Each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion object, intrusion location, and intrusion time of the corresponding intrusion event. For example, as shown in Figure 3, it can be seen that intrusion object A causes disturbance to sensing optical fibers 301 at locations ① and ② at times T1 and T2, respectively. If the two intrusion events corresponding to intrusion object A in Figure 3 have been processed by the network management system 304, and the network management system 304 has determined that the two intrusion events correspond to the same intrusion object and records the intrusion object as A (A is a name or number, etc.), then the first description information of the two intrusion events can be recorded as {intrusion object A, location ①, time T1} and {intrusion object A, location ②, time T2}, respectively.

[0082] For example, the historical early warning information may be one or more historical event information stored within the network management system.

[0083] In one possible implementation, the first descriptive information may further include the type and / or movement trajectory of the intrusion object corresponding to the intrusion event. For example, after security personnel receive a notification from the network management system and process the intrusion event, they can send information such as the actual type and movement trajectory of the corresponding intrusion object to the network management system for storage.

[0084] Step S402: Obtain the current warning information of the one or more warning units.

[0085] Specifically, the current warning information includes one or more current event information, and each current event information includes a second description of an intrusion event to be processed on one of the sensing optical fibers. The second description includes the intrusion location and intrusion time of the corresponding intrusion event. For example, as shown in Figure 3, it can be seen that intrusion object A causes disturbance to sensing optical fibers 301 at locations ① and ② at times T1 and T2, respectively. If the two intrusion events corresponding to intrusion object A in Figure 3 are still waiting for the network management system 304 to process, and the network management system 304 cannot determine whether the two intrusion events correspond to the same intrusion object, then the second description information of the two intrusion events can be recorded as {location ①, time T1} and {location ②, time T2}, respectively.

[0086] For example, the current warning information may be one or more current event information sent by various warning units and awaiting processing by the network management system.

[0087] In one possible implementation, the second descriptive information may further include the type of the intrusion object corresponding to the intrusion event. The type of intrusion object can be personnel or vehicles, etc. For example, as shown in Figure 3, intrusion object A disturbs the sensing fiber optic cable 301 at positions ① and ② at times T1 and T2, respectively. If the two intrusion events corresponding to intrusion object A in Figure 3 are still awaiting processing by the network management system 304, and the network management system 304 cannot determine whether the two intrusion events correspond to the same intrusion object, but the early warning unit can identify that the type of intrusion object A is personnel, then the second descriptive information of the two intrusion events can be recorded as {position ①, time T1, personnel} and {position ②, time T2, personnel}, respectively.

[0088] It should be noted that the type of intrusion object can correspond to the type of intrusion event. For example, when the types of intrusion events are excavator intrusion and personnel intrusion, the corresponding types of intrusion objects are excavator and personnel, respectively.

[0089] In one possible implementation, the second description information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event.

[0090] Step S403: Based on the historical warning information and the current warning information, determine the M intrusion objects corresponding to the one or more current event information, and determine the movement information of each of the M intrusion objects.

[0091] Specifically, the motion information includes the position change pattern of the corresponding intrusion object, where M is an integer greater than 0.

[0092] For example, each of the M intrusion objects may correspond to at least one intrusion event to be processed, that is, to at least one current event information.

[0093] In one possible implementation, determining the M intrusion objects corresponding to the one or more current event information based on the historical warning information and the current warning information includes: dividing the one or more current event information into one or more groups based on the historical warning information and the current warning information, each group including at least one current event information, and each intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; and determining the M intrusion objects based on the one or more groups.

[0094] For example, by analyzing instances of the correspondence between intrusion objects and intrusion events in the historical warning information, one or more current event information in the current warning information can be divided into one or more groups, that is, determining which current event information corresponds to the same intrusion object. For instance, if by analyzing one or more historical event information in the historical warning information, it can be found that when two processed intrusion events correspond to the same intrusion object, the difference in intrusion time between the two processed intrusion events is less than ΔT, and the distance between the intrusion locations is less than ΔS, then: the two current event information in the current warning information whose corresponding intrusion time difference is less than ΔT and whose intrusion location distance is less than ΔS can be grouped into the same group.

[0095] In one possible implementation, determining the movement information of each of the M intrusion objects includes: determining the movement trajectories of N intrusion objects among the M intrusion objects based on the historical warning information and the current warning information, where N is an integer greater than 0 and less than or equal to M. For example, if analysis shows that in the historical warning information, the intrusion object corresponding to the intrusion event with the intrusion location in region 1 will subsequently move to region 2, then the movement trajectory of the intrusion object corresponding to the intrusion event with the intrusion location in region 1 among the M intrusion objects can be predicted to be from region 1 to region 2.

[0096] Optionally, determining the movement trajectories of N intrusion objects out of the M intrusion objects based on the historical warning information and the current warning information includes: determining at least one historical event information that satisfies a first condition based on the historical warning information and the current warning information, and determining the current event information corresponding to each of the N intrusion objects; determining the movement trajectory of each of the N intrusion objects based on the at least one historical event information that satisfies the first condition and based on the current event information corresponding to each of the N intrusion objects.

[0097] Optionally, the first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0098] Optionally, the historical event information that satisfies the first condition also satisfies a second condition, wherein the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0099] In one possible implementation, determining the motion information of each of the M intrusion objects further includes: determining the position of each of the N intrusion objects at one or more moments based on the motion trajectories of the N intrusion objects. For example, the position at one or more moments can be represented as a pair of moments and positions, such as ((moment 1, position 1), (moment 2, position 2), ...).

[0100] In one possible implementation, determining the motion information of each of the M intrusion objects includes: determining the motion speed and direction of motion of L of the M intrusion objects based on the historical warning information and the current warning information, where L is an integer greater than 0 and less than or equal to M.

[0101] Optionally, the first description information further includes the movement speed and direction of the intrusion object corresponding to the corresponding intrusion event; determining the movement speed and direction of L intrusion objects among the M intrusion objects based on the historical event information and the warning information includes: determining at least one historical event information that satisfies a third condition based on the historical warning information and the current warning information, and determining the current event information corresponding to each of the L intrusion objects; determining the movement speed and direction of each of the L intrusion objects at one or more times based on the at least one historical event information that satisfies the third condition and based on the current event information corresponding to each of the L intrusion objects.

[0102] For example, after step S403 is executed, the fiber optic sensing early warning method may further include: sending a first request to a geographic information system (GIS) based on the movement trajectory of each of the N intrusion objects, wherein the GIS is communicatively connected to the network management system; receiving a response from the GIS to the first request, and generating a trajectory map for each of the N intrusion objects based on the response, wherein the trajectory map includes corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object. For example, the corresponding map information may include the display of locations, roads, etc., related to the movement trajectory, and the graphical representation of the movement trajectory may be displayed as a straight line, polyline, or curve representing the movement trajectory at the relevant locations and roads.

[0103] Optionally, after step S403 is performed, the fiber optic sensing early warning method may further include the following step S404:

[0104] Step S404: Based on the historical warning information and the current warning information, determine the probability of occurrence of one or more of the location change patterns for each of the K intrusion objects.

[0105] Specifically, the location change pattern refers to the movement trajectory of the corresponding intrusion object and / or the movement speed and direction of the corresponding intrusion object; the K intrusion objects are the intrusion objects among the M intrusion objects, where K is an integer greater than 0 and less than or equal to M. For example, if analysis shows that, in the historical warning information, among the intrusion objects corresponding to the intrusion event with the intrusion location in region 3, 90% will move to region 4 and 10% will move to region 5, then for the intrusion event with the intrusion location in region 3 among the M intrusion objects, the probability that the movement trajectory of the corresponding intrusion object is from region 3 to region 4 can be predicted as 90%, and the probability that it is from region 3 to region 5 can be predicted as 10%.

[0106] For example, based on the historical warning information and the current warning information, grouping one or more current event information in the current warning information, and determining the location change patterns such as the movement trajectory, speed, and direction of the intrusion object corresponding to the current event information, as well as the probability of occurrence of the location change patterns, can all be achieved by analyzing relevant instances in the historical warning information and making predictions based on the current warning information. The specific analysis and prediction process can be completed by executing a preset algorithm in the network management system, or by inputting the historical warning information and the current warning information into a neural network model or digital twin model in a third-party system. This application embodiment does not impose specific limitations on this. The third-party system can communicate with the network management system.

[0107] For example, the network management system can communicate with a third-party system. After step S401 is executed, the fiber optic sensing early warning method may further include: inputting the historical early warning information into a neural network model and / or a digital twin model in the third-party system. Specifically, the historical early warning information can be used to generate or train the neural network model, or to generate or adjust the digital twin model.

[0108] Please refer to Figure 5, which is a flowchart illustrating another fiber optic sensing early warning method provided in this application embodiment. This method can be applied to the system architecture described in Figure 3 above. The network management system 304 can be used to support and execute the method flow steps S503-S505, S501, S507, and S508 shown in Figure 5. The early warning unit 302 can be used to support and execute the method flow step S502 shown in Figure 5. The third-party system 305 may include the geographic information system and the line inspection system shown in Figure 5, and the geographic information system can be used to support and execute the method flow step S506 shown in Figure 5. The network management system 304 can communicate with the geographic information system, the line inspection system, and one or more early warning units 302. Each early warning unit 302 corresponds to at least one sensing fiber optic cable 301.

[0109] As shown in Figure 5, after acquiring historical early warning information and receiving current early warning information from the early warning unit, the network management system can determine M intrusion targets based on the historical and current early warning information, and determine the location change patterns, i.e., movement trajectories, of N of these intrusion targets. Then, the network management system can generate a trajectory map of these N intrusion targets through communication with a geographic information system. Since this trajectory map includes corresponding map information and a graphical representation of the movement trajectory, it is more intuitive and comprehensive. If the network management system sends a notification message containing this trajectory map to security personnel through the line patrol system, enabling security personnel to track and handle the intrusion targets according to the trajectory map, it will help accelerate the speed at which security personnel eliminate security risks. The following description, in conjunction with Figure 5, will consider multiple aspects, including the network management system side and the early warning unit side. Specifically, this fiber optic sensing early warning method can include the following steps S501-S508.

[0110] Step S501: The network management system obtains historical early warning information.

[0111] Specifically, the historical early warning information includes one or more historical event information, and each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion target, intrusion location and intrusion time of the corresponding intrusion event.

[0112] For example, the historical early warning information may be one or more historical event information stored within the network management system.

[0113] In one possible implementation, the first description information may further include the type and / or movement trajectory of the intrusion object corresponding to the intrusion event.

[0114] Step S502: The early warning unit sends the current early warning information to the network management system.

[0115] Specifically, the current warning information includes one or more current event information, and each current event information includes a second description of an intrusion event to be processed in one of the sensing optical fibers. The second description includes the intrusion location and intrusion time of the corresponding intrusion event.

[0116] In one possible implementation, the second description information may further include the type of the intrusion object corresponding to the intrusion event.

[0117] Step S503: The network management system determines M intrusion targets based on the historical warning information and the current warning information.

[0118] Specifically, the M intrusion objects correspond to one or more current event information in the current warning information, where M is an integer greater than 0.

[0119] For example, each of the M intrusion objects may correspond to at least one intrusion event to be processed, that is, to at least one current event information.

[0120] In one possible implementation, determining M intrusion objects based on the historical warning information and the current warning information includes: dividing one or more current event information in the current warning information into one or more groups based on the historical warning information and the current warning information, each group including at least one current event information, and the intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; determining the M intrusion objects based on the one or more groups.

[0121] Step S504: The network management system determines the movement trajectories of N intrusion targets based on the historical early warning information and the current early warning information.

[0122] Specifically, the N intrusion objects are the intrusion objects among the M intrusion objects, where N is an integer greater than 0 and less than or equal to M.

[0123] In one possible implementation, determining the movement trajectories of N intrusion objects based on the historical warning information and the current warning information includes: determining at least one historical event information that satisfies a first condition based on the historical warning information and the current warning information, and determining the current event information corresponding to each of the N intrusion objects; determining the movement trajectory of each of the N intrusion objects based on the at least one historical event information that satisfies the first condition and based on the current event information corresponding to each of the N intrusion objects.

[0124] Optionally, the first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0125] Optionally, the historical event information that satisfies the first condition also satisfies a second condition, wherein the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0126] Step S505: The network management system sends a first request to the geographic information system based on the movement trajectories of the N intrusion objects.

[0127] Specifically, the first request may include the movement trajectories of the N intrusion objects. For example, the first request may be sent to the geographic information system based on the movement trajectory of each of the N intrusion objects.

[0128] Step S506: The geographic information system sends response information corresponding to the first request to the network management system.

[0129] Specifically, the response information may include map information corresponding to the movement trajectories of the N intrusion objects.

[0130] Step S507: The network management system generates a trajectory map of the N intrusion objects based on the response information.

[0131] Specifically, the trajectory map may include corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object.

[0132] Step S508: The network management system sends a notification message to the line patrol system based on the current early warning information and the trajectory map of the N intrusion objects.

[0133] Specifically, the notification message may include one or more current event information from the current warning information, as well as a trajectory map including the N intrusion objects.

[0134] For example, before the above step S508 is performed, the fiber optic sensing early warning method may further include: determining the probability of occurrence of one or more of the motion trajectories of each of the N intrusion objects based on the historical early warning information and the current early warning information.

[0135] For example, the notification message may also include the probability of occurrence of one or more of the motion trajectories for each of the N intrusion objects.

[0136] Please refer to Figure 6, which is a flowchart illustrating another fiber optic sensing early warning method provided in this application embodiment. This method can be applied to the system architecture described in Figure 3 above. The network management system 304 can be used to support and execute the method flow steps S601 and S603-S606 shown in Figure 6. The early warning unit 302 can be used to support and execute the method flow step S602 shown in Figure 6. The third-party system 305 may include the line patrol system shown in Figure 6. The network management system 304 can communicate with the line patrol system and one or more early warning units 302. Each early warning unit 302 corresponds to at least one sensing fiber optic cable 301.

[0137] As shown in Figure 6, after acquiring historical early warning information and receiving current early warning information from the early warning unit, the network management system can determine M intrusion targets based on the historical and current early warning information, and determine the position change patterns, i.e., movement trajectories, of N of these intrusion targets. Then, based on these movement trajectories, the network management system can determine the location of each of the N intrusion targets at one or more times. If the network management system sends a notification message containing this location to security personnel through the line patrol system, enabling security personnel to track and handle the N intrusion targets according to this location, it simplifies the process of sending notification messages through the line patrol system and makes the notification message more concise and clear, reducing the difficulty for security personnel to understand the notification message and thus accelerating the speed at which security personnel eliminate security risks. The following description, in conjunction with Figure 6, will consider multiple aspects, including the network management system side and the early warning unit side. Specifically, this fiber optic sensing early warning method may include the following steps S601-S606.

[0138] Step S601: The network management system obtains historical early warning information.

[0139] Specifically, the historical early warning information includes one or more historical event information, and each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion target, intrusion location and intrusion time of the corresponding intrusion event.

[0140] Step S602: The early warning unit sends the current early warning information to the network management system.

[0141] Specifically, the current warning information includes one or more current event information, and each current event information includes a second description of an intrusion event to be processed in one of the sensing optical fibers. The second description includes the intrusion location and intrusion time of the corresponding intrusion event.

[0142] Step S603: The network management system determines M intrusion targets based on the historical warning information and the current warning information.

[0143] Specifically, the M intrusion objects correspond to one or more current event information in the current warning information, where M is an integer greater than 0.

[0144] Step S604: The network management system determines the movement trajectories of N intrusion targets based on the historical early warning information and the current early warning information.

[0145] Specifically, the N intrusion objects are the intrusion objects among the M intrusion objects, where N is an integer greater than 0 and less than or equal to M.

[0146] Step S605: Based on the movement trajectories of the N intrusion objects, the network management system determines the location of each of the N intrusion objects at one or more times.

[0147] Specifically, the position of one of the N intrusion objects at one or more times may be located within at least one of the movement trajectories of that intrusion object.

[0148] Step S606: The network management system sends a notification message to the line patrol system based on the current early warning information and the location of each of the N intrusion objects at one or more times.

[0149] Specifically, the notification message may include one or more current event information from the current warning information, as well as the location of each of the N intrusion objects at one or more times.

[0150] For example, before the above step S606 is performed, the fiber optic sensing early warning method may further include: determining the probability of occurrence of one or more of the motion trajectories of each of the N intrusion objects based on the historical early warning information and the current early warning information.

[0151] For example, the notification message may also include the probability that each of the N intrusion objects is in a corresponding position at one or more times, and the probability of being in a corresponding position may be the probability of the occurrence of the movement trajectory of that position.

[0152] Please refer to Figure 7, which is a flowchart illustrating another fiber optic sensing early warning method provided in this application embodiment. This method can be applied to the system architecture described in Figure 3 above. The network management system 304 can be used to support and execute the method flow steps S701 and S703-S705 shown in Figure 7. The early warning unit 302 can be used to support and execute the method flow step S702 shown in Figure 7. The third-party system 305 may include the line patrol system shown in Figure 7. The network management system 304 can communicate with the line patrol system and one or more early warning units 302. Each early warning unit 302 corresponds to at least one sensing fiber optic cable 301.

[0153] As shown in Figure 7, after acquiring historical early warning information and receiving current early warning information from the early warning unit, the network management system can identify M intrusion targets based on the historical and current early warning information. It can also accurately and quickly determine the positional change patterns, i.e., the movement speed and direction, of L of these intrusion targets. Subsequently, if the network management system sends a notification message containing this movement speed and direction to security personnel through the line patrol system, enabling them to track and handle the intrusion targets according to these speeds and directions, it will accelerate the speed at which security personnel eliminate security risks. The following description, in conjunction with Figure 7, will consider multiple aspects, including the network management system and the early warning unit. Specifically, this fiber optic sensing early warning method may include the following steps S701-S705.

[0154] Step S701: The network management system obtains historical early warning information.

[0155] Specifically, the historical early warning information includes one or more historical event information, and each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion target, intrusion location and intrusion time of the corresponding intrusion event.

[0156] In one possible implementation, the first description information may also include the movement speed and direction of the intrusion object corresponding to the intrusion event.

[0157] Step S702: The early warning unit sends the current early warning information to the network management system.

[0158] Specifically, the current warning information includes one or more current event information, and each current event information includes a second description of an intrusion event to be processed in one of the sensing optical fibers. The second description includes the intrusion location and intrusion time of the corresponding intrusion event.

[0159] Step S703: The network management system determines M intrusion targets based on the historical warning information and the current warning information.

[0160] Specifically, the M intrusion objects correspond to one or more current event information in the current warning information, where M is an integer greater than 0.

[0161] Step S704: The network management system determines the movement speed and direction of movement of L intrusion objects based on the historical warning information and the current warning information.

[0162] Specifically, the L intrusion objects are the intrusion objects among the M intrusion objects, where L is an integer greater than 0 and less than or equal to M.

[0163] For example, each of the L intrusion objects may correspond to at least two current event information, that is, correspond to at least two intrusion events to be processed.

[0164] Step S705: The network management system sends a notification message to the line patrol system based on the current early warning information and the movement speed and direction of the L intrusion objects.

[0165] Specifically, the notification message may include one or more current event information from the current warning information, as well as the movement speed and direction of the L intrusion objects.

[0166] For example, before step S705 is performed, the fiber optic sensing early warning method may further include: determining the probability of one or more of the movement speeds and directions of motion for each of the L intrusion objects based on the historical early warning information and the current early warning information.

[0167] For example, the notification message may also include the probability of occurrence of one or more of the movement speeds and directions for each of the L intrusion objects.

[0168] Please refer to Figure 8, which is a flowchart illustrating another fiber optic sensing early warning method provided in this application embodiment. This method can be applied to the system architecture described in Figure 3 above. The network management system 304 can be used to support and execute the method flow steps S801 and S803-S805 shown in Figure 8. The early warning unit 302 can be used to support and execute the method flow step S802 shown in Figure 8. The third-party system 305 may include the line patrol system shown in Figure 8. The network management system 304 can communicate with the line patrol system and one or more early warning units 302. Each early warning unit 302 corresponds to at least one sensing fiber optic cable 301.

[0169] As shown in Figure 8, after acquiring historical early warning information and receiving current early warning information from the early warning unit, the network management system can identify M intrusion targets based on the historical and current early warning information. If the current early warning information includes the movement speed and direction of K intrusion targets at at least one moment—meaning the early warning unit processes the relevant information transmitted by the sensing fiber to obtain not only the intrusion location and time of the corresponding intrusion event but also the movement speed and direction of the intrusion targets—then the network management system can quickly determine the movement speed and direction of the K intrusion targets. Furthermore, the network management system can determine the probability of at least one movement speed and direction for each of the K intrusion targets based on the historical and current early warning information. If the network management system sends a notification message containing the movement speed, direction, and probability of occurrence to security personnel through the line patrol system, it will help security personnel to track and handle intrusion targets more accurately and comprehensively, accelerating the elimination of security risks. The following description, in conjunction with Figure 8, will focus on multiple aspects, including the network management system and the early warning unit. The fiber optic sensing early warning method may specifically include the following steps S801-S805.

[0170] Step S801: The network management system obtains historical early warning information.

[0171] Specifically, the historical early warning information includes one or more historical event information, and each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion target, intrusion location and intrusion time of the corresponding intrusion event.

[0172] In one possible implementation, the first description information may further include the movement speed and direction of the intrusion object corresponding to the intrusion event.

[0173] Step S802: The early warning unit sends the current early warning information to the network management system.

[0174] Specifically, the current warning information includes one or more current event information, and each current event information includes a second description of an intrusion event to be processed on one of the sensing optical fibers. The second description includes the intrusion location and intrusion time of the corresponding intrusion event, as well as the movement speed and movement direction of the intrusion object corresponding to the corresponding intrusion event.

[0175] Step S803: The network management system determines M intrusion targets based on the historical warning information and the current warning information.

[0176] Specifically, the M intrusion objects correspond to one or more current event information in the current warning information, where M is an integer greater than 0.

[0177] Step S804: Based on the historical warning information and the current warning information, the network management system determines the probability of one or more movement speeds and directions of movement for each of the K intrusion objects.

[0178] Specifically, the K intrusion objects are the intrusion objects among the M intrusion objects, where K is an integer greater than 0 and less than or equal to M.

[0179] Step S805: The network management system sends a notification message to the line patrol system based on the current early warning information and the probability of occurrence.

[0180] Specifically, the notification message may include one or more current event information from the current warning information, and may also include one or more movement speeds and directions of movement for each of the K intrusion objects, as well as the corresponding probability of occurrence.

[0181] Based on the above system architecture, this application provides a network management device applied in the above system architecture. Please refer to Figure 9, which is a structural schematic diagram of a network management device provided in this application embodiment. As shown in Figure 9, the network management device 900 may include a first information acquisition module 901, a second information acquisition module 902, and an information processing module 903. Optionally, it may also include a graphical module 904 and a probability calculation module 905. The various modules in the network management device 900 can communicate and connect with each other.

[0182] The first information acquisition module 901 can be used to acquire historical early warning information of the one or more early warning units. The historical early warning information includes one or more historical event information. Each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description information includes the intrusion object, intrusion location and intrusion time of the corresponding intrusion event.

[0183] The second information acquisition module 902 can be used to acquire the current warning information of the one or more warning units. The current warning information includes one or more current event information. Each current event information includes a second description of an intrusion event to be processed on one of the sensing optical fibers. The second description information includes the intrusion location and intrusion time of the corresponding intrusion event.

[0184] The information processing module 903 can be used to determine M intrusion objects corresponding to one or more current event information based on the historical early warning information and the current early warning information, and to determine the motion information of each of the M intrusion objects, wherein the motion information includes the position change pattern of the corresponding intrusion object, and M is an integer greater than 0.

[0185] In one possible implementation, the information processing module 903 can be used to: divide the one or more current event information into one or more groups based on the historical warning information and the current warning information, each group including at least one current event information, and the intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; and determine the M intrusion objects based on the one or more groups.

[0186] In one possible implementation, the first description information further includes the movement trajectory of the intrusion object corresponding to the intrusion event; the information processing module 903 can be used to: determine the movement trajectories of N intrusion objects among the M intrusion objects based on the historical warning information and the current warning information, where N is an integer greater than 0 and less than or equal to M.

[0187] In one possible implementation, the information processing module 903 can be used to: determine at least one historical event information that satisfies a first condition based on the historical warning information and the current warning information, and determine the current event information corresponding to each of the N intrusion objects; and determine the movement trajectory of each of the N intrusion objects based on the at least one historical event information that satisfies the first condition and the current event information corresponding to each of the N intrusion objects.

[0188] In one possible implementation, the first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0189] In one possible implementation, the first description information and the second description information further include the type of the intrusion object corresponding to the corresponding intrusion event, and the historical event information that satisfies the first condition also satisfies the second condition, which is: the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

[0190] In one possible implementation, the information processing module 903 can be used to: determine the position of each of the N intrusion objects at one or more times based on the movement trajectories of the N intrusion objects.

[0191] In one possible implementation, the information processing module 903 can be used to: determine the movement speed and direction of movement of L of the M intrusion objects based on the historical warning information and the current warning information, where L is an integer greater than 0 and less than or equal to M.

[0192] In one possible implementation, the first description information further includes the movement speed and direction of the intrusion object corresponding to the intrusion event; the information processing module 903 can be used to: determine at least one historical event information that satisfies the third condition based on the historical warning information and the current warning information, and determine the current event information corresponding to each of the L intrusion objects; based on the at least one historical event information that satisfies the third condition, and based on the current event information corresponding to each of the L intrusion objects, determine the movement speed and direction of each of the L intrusion objects at one or more times.

[0193] In one possible implementation, the second description information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event.

[0194] In one possible implementation, the network management device further includes:

[0195] The graphical module 904 can be used to send a first request to a geographic information system based on the movement trajectory of each of the N intrusion objects, wherein the geographic information system is communicatively connected to the network management system; receive the response of the geographic information system to the first request, and generate a trajectory map of each of the N intrusion objects based on the response, wherein the trajectory map includes corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object.

[0196] In one possible implementation, the location change pattern is the movement trajectory of the corresponding intrusion target and / or the movement speed and direction of the corresponding intrusion target; the network management device further includes:

[0197] The probability calculation module 905 can be used to determine the probability of occurrence of one or more of the location change patterns of each of the K intrusion objects based on the historical warning information and the current warning information, wherein the K intrusion objects are the intrusion objects among the M intrusion objects, and K is an integer greater than 0 and less than or equal to M.

[0198] It is understood that the structure of the network management device in Figure 9 is only an exemplary implementation in the embodiments of this application, and the structure of the network management device in the embodiments of this application includes, but is not limited to, the above structure.

[0199] Please refer to Figure 10, which is a schematic diagram of another network management device provided in an embodiment of this application. The network management device 1000 includes at least one processor 1001, at least one memory 1002, and at least one communication interface 1003. In addition, the device may also include general components such as antennas, which will not be described in detail here.

[0200] The processor 1001 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the above-mentioned program.

[0201] The memory 1002 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory may exist independently and be connected to the processor via a bus. The memory may also be integrated with the processor.

[0202] Communication interface 1003 is used to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), core network, Wireless Local Area Networks (WLAN), etc.

[0203] The memory 1002 can be used to store the application code that executes the above scheme, and its execution is controlled by the processor 1001. The processor 1001 can be used to execute the application code stored in the memory 1002.

[0204] It should be noted that the code stored in memory 1002 can execute the fiber optic sensing early warning method provided in Figures 4-8 above. The functions of each functional unit in the network management device 1000 described in this application embodiment can be found in the relevant descriptions in the method embodiment in Figures 4-8 above, and will not be repeated here.

[0205] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0206] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0207] In the several embodiments provided in this application, it should be understood that the disclosed devices or apparatuses can be implemented in other ways. For example, the device or apparatus embodiments described above are merely illustrative. For instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of devices, apparatuses, or units may be electrical or other forms.

[0208] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0209] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0210] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium may include various media capable of storing program code, such as a USB flash drive, portable hard drive, magnetic disk, optical disk, read-only memory, or random access memory.

[0211] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A fiber optic sensing early warning method, characterized in that, The method is applied to a network management system, which is communicatively connected to one or more early warning units, each of which corresponds to at least one sensing optical fiber; the method includes: The historical warning information of the one or more warning units is obtained. The historical warning information includes one or more historical event information. Each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion object, intrusion location and intrusion time of the corresponding intrusion event. The current warning information of the one or more warning units is obtained. The current warning information includes one or more current event information. Each current event information includes a second description of an intrusion event to be processed by one of the sensing optical fibers. The second description information includes the intrusion location and intrusion time of the corresponding intrusion event. Based on the historical warning information and the current warning information, M intrusion objects corresponding to the one or more current event information are determined, and the motion information of each of the M intrusion objects is determined. The motion information includes the position change pattern of the corresponding intrusion object, and M is an integer greater than 0.

2. The method according to claim 1, characterized in that, The step of determining M intrusion objects corresponding to one or more current event information based on the historical early warning information and the current early warning information includes: Based on the historical warning information and the current warning information, the one or more current event information is divided into one or more groups, each group includes at least one current event information, and the intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; The M intrusion targets are determined based on the one or more groups.

3. The method according to claim 1 or 2, characterized in that, The first descriptive information also includes the movement trajectory of the intrusion object corresponding to the intrusion event; determining the movement information of each of the M intrusion objects includes: Based on the historical warning information and the current warning information, the movement trajectories of N intrusion objects out of the M intrusion objects are determined, where N is an integer greater than 0 and less than or equal to M.

4. The method according to claim 3, characterized in that, Determining the movement trajectories of N intrusion objects out of the M intrusion objects based on the historical early warning information and the current early warning information includes: Based on the historical warning information and the current warning information, at least one historical event information that satisfies the first condition is determined, and the current event information corresponding to each of the N intrusion objects is determined; Based on the historical event information that satisfies at least one of the first conditions, and based on the current event information corresponding to each of the N intrusion objects, the movement trajectory of each of the N intrusion objects is determined.

5. The method according to claim 4, characterized in that, The first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

6. The method according to claim 4 or 5, characterized in that, The first description information and the second description information also include the type of the intrusion object corresponding to the corresponding intrusion event. The historical event information that satisfies the first condition also satisfies the second condition, which is: the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

7. The method according to any one of claims 3-6, characterized in that, Determining the motion information of each of the M intrusion objects further includes: Based on the movement trajectories of the N intrusion objects, determine the position of each of the N intrusion objects at one or more times.

8. The method according to any one of claims 3-6, characterized in that, After determining the motion information of each of the M intrusion targets, the method further includes: Based on the movement trajectory of each of the N intrusion objects, a first request is sent to the geographic information system, which is communicatively connected to the network management system. The system receives the response from the geographic information system to the first request and generates a trajectory map for each of the N intrusion objects based on the response. The trajectory map includes the corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object.

9. The method according to any one of claims 1-8, characterized in that, Determining the motion information of each of the M intrusion objects includes: Based on the historical warning information and the current warning information, determine the movement speed and direction of movement of L intrusion objects out of the M intrusion objects, where L is an integer greater than 0 and less than or equal to M.

10. The method according to claim 9, characterized in that, The first descriptive information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event; determining the movement speed and direction of L intrusion objects out of the M intrusion objects based on the historical event information and the early warning information includes: Based on the historical warning information and the current warning information, at least one historical event information that satisfies the third condition is determined, and the current event information corresponding to each of the L intrusion objects is determined; Based on the historical event information that satisfies at least one of the third conditions, and based on the current event information corresponding to each of the L intrusion objects, determine the speed and direction of movement of each of the L intrusion objects at one or more times.

11. The method according to claims 1-8, characterized in that, The second descriptive information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event.

12. The method according to any one of claims 1-11, characterized in that, The position change pattern is the movement trajectory of the corresponding intrusion object and / or the movement speed and direction of the corresponding intrusion object; After determining the motion information of each of the M intrusion targets, the method further includes: Based on the historical warning information and the current warning information, determine the probability of occurrence of one or more of the aforementioned location change patterns for each of the K intrusion objects, where the K intrusion objects are the intrusion objects among the M intrusion objects, and K is an integer greater than 0 and less than or equal to M.

13. A network management device, characterized in that, The network management device is communicatively connected to one or more early warning units, and each early warning unit corresponds to at least one sensing optical fiber. The network management device includes: The first information acquisition module is used to acquire historical early warning information of the one or more early warning units. The historical early warning information includes one or more historical event information. Each historical event information includes a first description of a processed intrusion event of one of the sensing optical fibers. The first description includes the intrusion object, intrusion location and intrusion time of the corresponding intrusion event. The second information acquisition module is used to acquire the current warning information of the one or more warning units. The current warning information includes one or more current event information. Each current event information includes a second description of an intrusion event to be processed on one of the sensing optical fibers. The second description information includes the intrusion location and intrusion time of the corresponding intrusion event. The information processing module is used to determine M intrusion objects corresponding to the one or more current event information based on the historical early warning information and the current early warning information, and to determine the motion information of each of the M intrusion objects, wherein the motion information includes the position change pattern of the corresponding intrusion object, and M is an integer greater than 0.

14. The device according to claim 13, characterized in that, The information processing module is specifically used for: Based on the historical warning information and the current warning information, the one or more current event information is divided into one or more groups, each group includes at least one current event information, and the intrusion event corresponding to each current event information in each group corresponds to the same intrusion object; The M intrusion targets are determined based on the one or more groups.

15. The device according to claim 13 or 14, characterized in that, The first descriptive information also includes the movement trajectory of the intrusion object corresponding to the intrusion event; the information processing module is specifically used for: Based on the historical warning information and the current warning information, the movement trajectories of N intrusion objects out of the M intrusion objects are determined, where N is an integer greater than 0 and less than or equal to M.

16. The device according to claim 15, characterized in that, The information processing module is specifically used for: Based on the historical warning information and the current warning information, at least one historical event information that satisfies the first condition is determined, and the current event information corresponding to each of the N intrusion objects is determined; Based on the historical event information that satisfies at least one of the first conditions, and based on the current event information corresponding to each of the N intrusion objects, the movement trajectory of each of the N intrusion objects is determined.

17. The device according to claim 16, characterized in that, The first condition is: the distance between the corresponding intrusion event and the intrusion location of at least one first intrusion event is less than or equal to a preset distance; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

18. The device according to claim 16 or 17, characterized in that, The first description information and the second description information also include the type of the intrusion object corresponding to the corresponding intrusion event. The historical event information that satisfies the first condition also satisfies the second condition, which is: the corresponding intrusion event corresponds to the same type of intrusion object as at least one first intrusion event; the first intrusion event is the intrusion event to be processed, and each first intrusion event corresponds to one of the N intrusion objects.

19. The device according to any one of claims 15-18, characterized in that, The information processing module is also used for: Based on the movement trajectories of the N intrusion objects, determine the position of each of the N intrusion objects at one or more times.

20. The device according to any one of claims 15-18, characterized in that, The network management device also includes: A graphical module is used to send a first request to a geographic information system based on the movement trajectory of each of the N intrusion objects, wherein the geographic information system is communicatively connected to the network management system. The system receives the response from the geographic information system to the first request and generates a trajectory map for each of the N intrusion objects based on the response. The trajectory map includes the corresponding map information and a graphical representation of the movement trajectory of the corresponding intrusion object.

21. The device according to any one of claims 13-20, characterized in that, The information processing module is specifically used for: Based on the historical warning information and the current warning information, determine the movement speed and direction of movement of L intrusion objects out of the M intrusion objects, where L is an integer greater than 0 and less than or equal to M.

22. The device according to claim 21, characterized in that, The first descriptive information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event; the information processing module is specifically used for: Based on the historical warning information and the current warning information, at least one historical event information that satisfies the third condition is determined, and the current event information corresponding to each of the L intrusion objects is determined; Based on the historical event information that satisfies at least one of the third conditions, and based on the current event information corresponding to each of the L intrusion objects, determine the speed and direction of movement of each of the L intrusion objects at one or more times.

23. The method according to claims 13-20, characterized in that, The second descriptive information also includes the movement speed and direction of the intrusion object corresponding to the intrusion event.

24. The device according to any one of claims 13-23, characterized in that, The position change pattern is the movement trajectory of the corresponding intrusion object and / or the movement speed and direction of the corresponding intrusion object; The network management device also includes: The probability calculation module is used to determine the probability of occurrence of one or more of the location change patterns of each of the K intrusion objects based on the historical warning information and the current warning information, wherein the K intrusion objects are the intrusion objects among the M intrusion objects, and K is an integer greater than 0 and less than or equal to M.

25. An electronic device, characterized in that, The electronic device includes a processor and an interface circuit, the processor being configured to communicate with other devices via the interface circuit, thereby enabling the electronic device to implement the method as described in any one of claims 1-12.

26. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the fiber optic sensing early warning method as described in any one of claims 1-12.

27. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program, which, when executed, performs the method according to any one of claims 1-12.

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