Intrusion identification system, method and equipment based on meteorological monitoring

Abstract

The invention discloses an intrusion identification system, method and device based on meteorological monitoring, and relates to the technical field of security monitoring. Comprising a fence and an intrusion detection device arranged on the fence, and further comprises a weather sensing system and an edge control unit which are matched with the fence, and the intrusion detection device and the weather sensing system are connected with the edge control unit; the intrusion detection device is used for collecting vibration data on the fence and sending the vibration data to the edge control unit; the meteorological sensing system is used for collecting meteorological data of an area where a fence is located and sending the meteorological data to the edge control unit. And the edge control unit corrects the vibration data according to the received meteorological data, and completes intrusion detection analysis according to the corrected vibration data. By adopting the setting form, the detection means are increased, the corrected detection data are calibrated, and the risks of misjudgment and missing detection are reduced.

Description

Technical Field

[0001] The present application relates to the field of security monitoring technology, and in particular to an intrusion identification system, method and device based on meteorological monitoring. Background Art

[0002] Intrusion monitoring refers to monitoring external objects that enter the designated area without permission, and giving an alarm to the intruder or reminding the supervisor. At present, the intrusion monitoring system has been widely used in military, civil aviation, judicial, civil and other fields.

[0003] Intrusion monitoring systems usually include key components such as perception systems and monitoring alarm systems. The main task of the perception system is to monitor activities in the area where the fence is located, and the monitoring system is used to analyze the data captured by the perception system to identify possible intrusion events. The goal of traditional fence systems is to quickly issue an alarm when the system identifies a potential intrusion threat, notifying security personnel to take measures to prevent illegal entry and other potential threat events to ensure the safety of the fence.

[0004] However, the existing intrusion monitoring systems have a single monitoring method and cannot cope with diverse intrusion methods. The system is easily affected by environmental factors, technical limitations and camouflage, and cannot calibrate detection data, which increases the risk of misjudgment and missed detection and limits the overall effectiveness of the intrusion monitoring system. Summary of the invention

[0005] The purpose of this application is to provide an intrusion identification method, system and equipment based on meteorological monitoring, which increases the detection means and calibrates and corrects the detection data, thereby reducing the risk of misjudgment and missed detection.

[0006] In the first aspect, the present application provides an intrusion identification system based on meteorological monitoring, including: a fence, an intrusion detection device arranged on the fence, and also a meteorological sensor system and an edge control unit matched with the fence, the intrusion detection device and the meteorological sensor system are connected to the edge control unit; the intrusion detection device is used to collect vibration data on the fence, and send the vibration data to the edge control unit; the meteorological sensor system is used to collect meteorological data of the area where the fence is located, and send the meteorological data to the edge control unit; the edge control unit corrects the vibration data according to the received meteorological data, and completes the intrusion detection analysis according to the corrected vibration data.

[0007] Optionally, the intrusion detection device includes a first sensing unit for collecting image data and first vibration data and / or a second sensing unit for collecting second vibration data.

[0008] Optionally, the distance between two adjacent first sensing units is l≤L1; the number of second sensing units arranged between two adjacent first sensing units is n, and n satisfies (n+1)L2≥L1, where L1 is the image acquisition limit, L2 is the vibration acquisition limit, and n is a natural number.

[0009] Optionally, the step of obtaining a preset vibration range according to the meteorological data and the trained learning model includes:

[0010] Obtain wind direction information and wind speed information according to the meteorological data;

[0011] According to the wind direction information, define the part of the fence whose extension direction is perpendicular to the wind direction as the windward fence, mark at least one intrusion device on the windward fence as the windward intrusion device, define the part of the fence whose extension direction is parallel to the wind direction as the downwind fence, mark at least one intrusion device on the downwind fence as the downwind intrusion device;

[0012] According to the wind direction information, the wind speed information and the learning model, the preset vibration ranges for collecting vibration data of the headwind intrusion device and the downwind intrusion device are respectively obtained.

[0013] Optionally, the step of comparing the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range further includes:

[0014] Comparing the vibration data with the preset vibration range to obtain secondary data in the vibration data that is within the preset vibration range;

[0015] According to the secondary data, calculating the standard deviation of the secondary data and evaluating its dispersion;

[0016] According to the discreteness analysis result, determining whether there is outlier data;

[0017] If not, marking the secondary data as normal data;

[0018] If so, the source of the outlier data is traced back and the corresponding intrusion device is marked as the first outlier device.

[0019] Optionally, if yes, tracing back the source of the outlier data and marking the corresponding intrusion device as the first outlier device further includes:

[0020] According to the first outlier device, obtaining at least one second outlier device associated with the first outlier device;

[0021] The cause of the outlier data is analyzed based on the operation data of the second outlier device and the first outlier device.

[0022] Optionally, the step of obtaining an intrusion detection analysis result according to the abnormal data further includes:

[0023] Acquire first abnormal data in the vibration data that is smaller than the preset vibration range, and trace the source of the first abnormal data;

[0024] If the first abnormal data source is located in an isolated first intrusion collection device, marking the first intrusion collection device and outputting a first fault alarm;

[0025] If the first abnormal data comes from multiple consecutive second intrusion collection devices, the fence where the second intrusion collection device is located is marked and a second fault alarm is output.

[0026] Optionally, the step of obtaining an intrusion detection analysis result according to the abnormal data further includes:

[0027] Acquire second abnormal data in the vibration data that is greater than the preset vibration range, and trace the source of the second abnormal data;

[0028] If the abnormal data originates from an isolated third intrusion collection device, outputting a first intrusion alarm;

[0029] If the abnormal data is from a plurality of consecutive fourth intrusion collection devices, acquiring image information of the area where the fourth intrusion collection device is located;

[0030] Based on the image information, a second intrusion alarm or a third fault alarm indicating that a fence where the fourth intrusion collection device is located is faulty is output.

[0031] Optionally, the step of outputting a second intrusion alarm or a third fault alarm of a fence failure where the fourth intrusion collection device is located based on the image information includes:

[0032] Preprocessing the image information to obtain a target image;

[0033] Extracting key features according to the target image;

[0034] According to the key features, identify the object or behavior in the target image and output the recognition result;

[0035] Based on the recognition results, determine whether there is intrusion or fence failure;

[0036] If an intrusion behavior is identified, a second intrusion alarm is output;

[0037] If a fence failure is identified, a third failure alarm indicating that the fence where the fourth intrusion collection device is located is faulty is output.

[0038] In a third aspect, the present application also provides an intrusion identification device based on meteorological monitoring, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned intrusion identification method based on meteorological monitoring.

[0039] The beneficial effects of this application include:

[0040] The present application provides an intrusion identification system, method and device based on meteorological monitoring, which matches a meteorological sensing system and an edge control unit with a fence, further sets an intrusion detection device on the fence to collect vibration data on the fence, and sends the vibration data to the edge control unit. The meteorological sensing system collects meteorological data of the area where the fence is located, and sends the meteorological data to the edge control unit. The edge control unit corrects the vibration data according to the meteorological detection data, and completes the intrusion detection analysis according to the corrected vibration data. The above-mentioned setting form increases the detection means, calibrates the corrected detection data, and reduces the risk of misjudgment and missed detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 This is a schematic diagram of the structure of an intrusion identification system based on meteorological monitoring in this application;

[0043] Figure 2 This is a schematic diagram of the structure of the first sensor unit of the present application;

[0044] Figure 3 This is a schematic diagram of the structure of the second sensor unit of the present application;

[0045] Figure 4 A schematic diagram of a flow chart of an intrusion identification method based on meteorological monitoring in this application;

[0046] Figure 5 This is a schematic diagram of the structure of the fence for this application;

[0047] Figure 6 is a first cross-sectional schematic diagram of the connection assembly of the present application;

[0048] Figure 7 This is a second cross-sectional schematic diagram of the connection assembly of the present application.

[0049] Icons: 100-intrusion detection device; 110-connecting piece; 111-accommodating chamber; 112-connecting groove; 120-pull rod; 121-bending portion; 130-hook unit; 131-connecting rod; 132-guide rod; 133-guide block; 134-compression spring; 140-driving block; 141-driving surface; 142-guide slope; 150-elastic abutment unit; 151-positioning plate; 152-elastic plate; 200-meteorological sensing system; 300-edge control unit; 400-fence.

[0050] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0052] It should be noted that all directional indications in the embodiments of the present application (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0053] In this application, unless otherwise clearly specified and limited, the terms "connection", "fixation", etc. should be understood in a broad sense. For example, "fixation" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0054] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0055] The existing intrusion monitoring system has a single monitoring method and cannot cope with diversified intrusion methods. The system is easily affected by environmental factors, technical limitations and disguises, and cannot calibrate the detection data, which increases the risk of misjudgment and missed detection, and limits the overall effectiveness of the intrusion monitoring system. In view of the above problems, the embodiments of the present application provide the following technical solutions to overcome the above problems.

[0056] Example 1

[0057] For easier understanding, please refer to Figure 1 The present application provides an intrusion identification system based on meteorological monitoring, including: a fence 400, an intrusion detection device 100 arranged on the fence 400, and also including a meteorological sensor system 200 and an edge control unit 300 matched with the fence 400, the intrusion detection device 100 and the meteorological sensor system 200 are connected to the edge control unit; the intrusion detection device 100 is used to collect vibration data on the fence 400, and send the vibration data to the edge control unit 300; the meteorological sensor system 200 is used to collect meteorological data in the area where the fence 400 is located, and send the meteorological data to the edge control unit 300; the edge control unit 300 corrects the vibration data according to the received meteorological data, and completes the intrusion detection analysis according to the corrected vibration data.

[0058] Specifically, by setting the meteorological sensor system 200 and the edge control unit 300 to match the fence 400, the intrusion detection device 100 is further set on the fence 400 to collect vibration data on the fence 400 and send the vibration data to the edge control unit 300. The meteorological sensor system 200 collects meteorological data in the area where the fence 400 is located, and sends the meteorological data to the edge control unit 300. The edge control unit 300 corrects the vibration data according to the meteorological detection data, and completes the intrusion detection analysis according to the corrected vibration data. The above-mentioned setting form increases the detection means, calibrates the corrected detection data, and reduces the risk of misjudgment and missed detection.

[0059] In the embodiment of the present application, the intrusion detection device 100 includes a first sensing unit for collecting image data and first vibration data and / or a second sensing unit for collecting second vibration data.

[0060] Specifically, the intrusion detection device 100 set on the fence 400 can use only the first sensor unit that can collect image data and first vibration data, or only the second sensor unit that can collect second vibration data, or both the first sensor unit and the second sensor unit.

[0061] It should be noted that the setting form of the intrusion detection device 100 is relatively flexible and can be arranged according to actual conditions and needs, wherein the image data is the image data collected by the first sensing unit and enters the image acquisition limit, the first vibration data is the vibration data of the fence 400 collected by the first sensor, and the second vibration data is the vibration data of the fence 400 collected by the second sensing unit.

[0062] In the embodiment of the present application, the distance between the two adjacent first sensing units is l≤L1; the number of second sensing units arranged between the two adjacent first sensing units is n, and n satisfies (n+1)L2≥L1, where L1 is the image acquisition limit, L2 is the vibration acquisition limit, and n is a natural number.

[0063] It is understandable that in order to ensure that the arrangement density of the sensor units is reduced without reducing the monitoring accuracy, the arrangement condition of the first sensor units must meet: l≤L1, where l represents the distance between two adjacent first sensor units, and L1 represents the image acquisition limit of the first sensor unit. With the above-mentioned setting method, when there is no blind spot for image acquisition in the fence 400, the number of the first sensor units is reduced to the maximum extent.

[0064] The arrangement condition of the second sensor unit must satisfy (n+1)L2≥L1. It should be noted that the second sensor unit is arranged between two adjacent first sensor units. Wherein, L2 represents the vibration acquisition limit of the second sensor unit, L1 represents the image acquisition limit of the first sensor unit, and n is a natural number. With the above-mentioned arrangement, when there is no vibration acquisition blind spot in the fence 400, the number of second sensor units is reduced to the maximum extent, thereby reducing the number of intrusion detection devices in the entire system, reducing the communication pressure and cost of the entire system, and enhancing the stability and reliability of the system.

[0065] Example 2

[0066] Based on Example 1, for ease of understanding, please refer to Figure 2 and Figure 3 The first sensing unit includes a visual detection module, a first vibration detection module, a first storage module, a first micro-control module and a first power supply module.

[0067] Specifically, the first sensing unit includes a visual detection module, a first vibration detection module, a first storage module, a first microcontroller module and a first power supply module. The modules cooperate with each other to realize the collection and transmission of image data and first vibration data.

[0068] The visual detection module is used to capture the target image of the object that enters the image acquisition limit and send the target image to the first microcontroller module. The visual detection module is the core part of the first sensing unit and is responsible for capturing and processing visual information. The visual detection module is a high-resolution thermal imaging sensor or infrared camera, which is used to capture images within the image acquisition limit. The thermal imaging sensor can detect temperature distribution and provide target recognition in low light or dark conditions, including objects with different temperature characteristics. The infrared camera is used to capture infrared images and is widely used in night vision and security monitoring.

[0069] The first vibration detection module is used to detect vibrations on the fence 400, generate first vibration data, and send the first vibration data to the first microcontroller module. The first vibration detection module can be divided into two types: infrared auxiliary vibration sensors and thermal imaging auxiliary vibration sensors. The auxiliary vibration sensor contains multiple important components, each of which plays an important role in the efficient operation of the system, ensuring that the system can efficiently monitor intrusion events, record relevant data, and interact effectively with other systems or devices. Auxiliary vibration sensors mostly use three-axis accelerometers to measure weak vibrations on the fence. By analyzing the characteristics of the vibration signal, such as amplitude and frequency, the system can distinguish between normal environmental vibrations and vibrations caused by potential intrusions. By monitoring these characteristics, it helps to determine the activities of the intruder and detect whether the intruder is trying to cross the fence 400 or cause damage. These vibration signals are crucial for detecting vibration events that may be related to intrusions.

[0070] The first microcontroller module is used to receive the target image sent by the visual detection module and generate image data; send the image data to the edge control unit 300 via Ethernet; receive the first vibration data sent by the first vibration detection module; send the first vibration data to the edge control unit 300 via Ethernet. The first microcontroller module includes a first communication module, which is used for real-time communication between modules. The first microcontroller is the intelligent core of the first sensing unit, which coordinates the work of each component and can use an STM32F407ZET6 single-chip microcomputer. The role of the first microcontroller is not limited to data transmission. It also undertakes the tasks of collecting, controlling, processing and communicating vibration data, and can be responsible for simple vibration detection algorithms, thereby assisting the system to make decisions in a timely manner.

[0071] The first storage module is used to store configuration data for quick configuration of each module. The first storage module is used to record and store configuration data for quick configuration of modules. These data include various parameters, settings and status information, which enable the device to operate in different environments and make adaptive adjustments according to needs to improve the performance and efficiency of the device.

[0072] The first power supply module: used to power each module. The first power supply module supports optional independent power supply and POE (Power over Ethernet), that is, Ethernet power supply. The POE power supply method allows power to be transmitted through the Ethernet data line to provide power for network devices. It transmits power and data to the sensor together through a standard Ethernet cable. POE power supply helps simplify the installation and management of network equipment, reduces messy cable wiring, and improves the reliability of equipment.

[0073] In this embodiment, the second sensing unit includes a second vibration detection module, a second storage module, a second micro-control module, a second power supply module, a light source inspection module and a fill light module.

[0074] The second vibration detection module is used to detect the vibration on the fence 400, generate second vibration data, and send the second vibration data to the second micro control module.

[0075] The second microcontroller module is used to receive the second vibration data sent by the second vibration detection module and send the second vibration data to the edge control unit 300 via the CAN bus. The second microcontroller module includes a second communication module, which is used for real-time communication between modules.

[0076] The second storage module is used to store configuration data so as to quickly configure each module.

[0077] The second power supply module is used to supply power to each module.

[0078] Light source inspection module: used to detect whether the ambient light meets the working requirements of the first sensing unit; when the light is insufficient, generate a light control instruction; send the light control instruction to the fill light module. Specifically, the light source inspection module is an important component of the second sensing unit. It is responsible for monitoring whether the fill light is normal and detecting whether the ambient light meets the working requirements of the visual detection module. Once insufficient light is detected, especially at night or in dim environments, the light source inspection automatically triggers the turn-on of the fill light to improve the visibility of the target area and ensure high-quality image capture. This automated process ensures that the system can operate reliably under various lighting conditions, provide clear visual information, and effectively respond to intrusion incidents. The light source inspection and fill light work together to maintain the efficiency and accuracy of the system.

[0079] Fill light module: used to receive the light control instruction sent by the light source inspection module; execute the light control instruction to fill light the environment. The fill light module is a lighting tool used to assist infrared cameras or night vision equipment. Its main function is to provide an infrared light source in low light or completely dark conditions to improve the visibility of infrared cameras. The infrared light generated by the infrared fill light is invisible to the human eye, but it is very useful for infrared cameras. It can illuminate the scene and capture high-quality infrared images, allowing the device to clearly see the target in a dark environment and improve the effectiveness of observation and monitoring. The filling light can be turned on by the light source inspection unit, or it can be triggered by the edge control unit 300 through the communication interface.

[0080] Among them, the functions and principles of the second vibration detection module, the second storage module, the second microcontroller module and the second power supply module are the same as those of the first vibration detection module, the first storage module, the first microcontroller module and the first power supply module in the above-mentioned embodiment, and are not described in detail here. In this embodiment, the second microcontroller can adopt the STM32F103T8U6 single-chip microcomputer.

[0081] Example 3

[0082] Based on Example 1 and Example 2, the meteorological sensing system 200 in this embodiment includes a temperature acquisition module, a humidity acquisition module, an air pressure acquisition module, a wind speed acquisition module, a precipitation acquisition module, a third storage module, a third microcontroller module and a third power supply module.

[0083] Wherein, the temperature acquisition module is used to collect the temperature value of the area where the fence 400 is located, and send the temperature value to the third micro-control module.

[0084] Humidity collection module: used to collect the humidity value of the area where the fence 400 is located, and send the humidity value to the third micro-control module.

[0085] Air pressure collection module: used to collect the air pressure value of the area where the fence 400 is located, and send the air pressure value to the third micro-control module.

[0086] Wind speed collection module: used to collect the wind speed value of the area where the fence 400 is located, and send the wind speed value to the third micro-control module.

[0087] Precipitation collection module: used to collect the precipitation in the area where the fence 400 is located; and send the precipitation to the third micro-control module.

[0088] The third storage module is used to store configuration data so as to quickly configure each module.

[0089] The third power supply module is used to supply power to each module.

[0090] The third microcontroller module is used to receive the temperature value, generate temperature simulation data according to the temperature value, and send the temperature simulation data to the edge control unit 300 via Ethernet; to receive the humidity value, generate humidity simulation data according to the humidity value, and send the temperature simulation data to the edge control unit 300 via Ethernet; to receive the air pressure value, generate air pressure simulation data according to the air pressure value, and send the air pressure simulation data to the edge control unit 300 via Ethernet; to receive the wind speed value, generate wind speed simulation data according to the wind speed value, and send the wind speed simulation data to the edge control unit 300 via Ethernet; to receive the precipitation, generate precipitation simulation data according to the precipitation, and send the precipitation simulation data to the edge control unit 300 via Ethernet. The third microcontroller module includes a third communication module, and the third communication module is used for real-time communication between modules.

[0091] Example 4

[0092] This embodiment also provides an intrusion identification method based on meteorological monitoring, comprising the following steps:

[0093] S10. Obtain historical vibration data collected by the intrusion device, and train a learning model based on the historical vibration data and corresponding historical meteorological data.

[0094] Specifically, collect historical vibration data collected by the intrusion device in a certain period of time in the past, including but not limited to amplitude, frequency, and vibration time, as well as historical meteorological data recorded by the meteorological sensor system in the same period of time, including but not limited to wind speed, wind direction, rainfall, temperature, humidity, etc. Clean the collected historical data to remove noise and outliers to ensure data quality. Extract key features from the preprocessed historical data, such as vibration frequency, amplitude, and changing trends of meteorological conditions. Use the extracted features and known intrusion events or normal states in the historical data to train machine learning models (such as neural networks, decision trees, support vector machines, etc.) so that the model can learn the relationship between vibration data and meteorological data and identify potential intrusion patterns.

[0095] S20. Acquire vibration data collected by the intrusion device and meteorological data collected by the meteorological sensor system.

[0096] Specifically, the vibration data of the current environment is collected in real time through the intrusion device, and the real-time meteorological data is obtained from the meteorological sensor system simultaneously.

[0097] S30: acquiring a preset vibration range according to the meteorological data and the trained learning model.

[0098] Specifically, the meteorological data collected in real time is input into the trained learning model, and the model outputs the expected vibration range under the current meteorological conditions. Based on the model prediction results, a reasonable preset vibration range (i.e., vibration threshold) is set, which should cover the vibration fluctuations under normal meteorological conditions while excluding false alarms.

[0099] S40: Compare the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range.

[0100] Specifically, the vibration data collected in real time is compared with the preset vibration range. Abnormal data points in the vibration data that exceed the preset vibration range are identified. The data in the vibration data that is within the preset vibration range is normal data, which may be caused by the wind in the environment causing the fence to vibrate. This part of normal data can be ignored, and there is no need to analyze and process the normal data separately.

[0101] S50: Obtain intrusion detection analysis results based on the abnormal data.

[0102] Specifically, the identified abnormal data is analyzed in depth, including the frequency, duration, and correlation with meteorological changes of the abnormalities. Based on the analysis results of the abnormal data and the preset intrusion judgment rules, it is determined whether there is an intrusion behavior. An intrusion detection analysis report is generated, including the time, location, possible type, and recommended countermeasures of the intrusion, and relevant personnel are notified in a timely manner through the user interface, email, or SMS.

[0103] Example 5

[0104] Based on Example 4, this embodiment further provides an intrusion identification method based on meteorological monitoring, comprising the following steps:

[0105] S10. Obtain historical vibration data collected by the intrusion device, and train a learning model based on the historical vibration data and corresponding historical meteorological data.

[0106] S20. Acquire vibration data collected by the intrusion device and meteorological data collected by the meteorological sensor system.

[0107] S30: acquiring a preset vibration range according to the meteorological data and the trained learning model.

[0108] Optionally, obtaining wind direction information and wind speed information according to the meteorological data;

[0109] S31. According to the wind direction information, define the part of the fence whose extension direction is perpendicular to the wind direction as the windward fence, mark at least one intrusion device on the windward fence as the windward intrusion device, define the part of the fence whose extension direction is parallel to the wind direction as the downwind fence, and mark at least one intrusion device on the downwind fence as the downwind intrusion device;

[0110] Specifically, according to the wind direction information, the fence is divided into two parts: the part extending perpendicular to the wind direction is defined as the "windward fence", which will directly face the impact of the wind; the part extending parallel to the wind direction is defined as the "downwind fence", which is relatively less affected by the wind. On the windward fence, at least one intrusion device is selected as the "windward intrusion device", which may be more susceptible to false alarms caused by wind or require special attention; on the downwind fence, at least one intrusion device is also selected as the "downwind intrusion device" to compare and verify the performance of the devices under different wind direction conditions.

[0111] S32. According to the wind direction information, the wind speed information and the learning model, respectively obtain the preset vibration ranges for collecting vibration data of the headwind intrusion device and the downwind intrusion device.

[0112] Specifically, for the headwind intrusion device, the preset vibration range for collecting vibration data of the device under given conditions is calculated based on the current wind direction information and wind speed information, as well as the predictive ability of the learning model. This range should take into account the increase in vibration that may be caused by the direct impact of wind on the fence; for the downwind intrusion device, the wind direction information, wind speed information and learning model are also used, but because it is less affected by wind, the preset vibration range may be reduced accordingly or maintained at a lower level. The calculated preset vibration range is applied to the actual intrusion detection system as a reference for determining whether the vibration signal is abnormal. When the actual vibration data exceeds the preset range, the system may trigger an alarm or perform further analysis and processing.

[0113] S40: Compare the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range.

[0114] Optionally, the step of comparing the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range further includes:

[0115] S41, comparing the vibration data with the preset vibration range to obtain secondary data in the vibration data that is within the preset vibration range;

[0116] Specifically, first, the real-time collected vibration data is compared one by one with the preset vibration range previously determined based on the meteorological data and the learning model, and the data within the preset vibration range is selected from the vibration data, which is called "secondary data".

[0117] S42, calculating the standard deviation of the secondary data according to the secondary data, and evaluating its discreteness;

[0118] Specifically, for the selected secondary data, calculate its standard deviation. Standard deviation is an important indicator to measure the degree of data dispersion, which reflects the degree of deviation of data points from the mean. According to the calculated standard deviation, evaluate the dispersion of secondary data. If the standard deviation is large, it means that the degree of dispersion between data points is high; otherwise, it means that the data points are relatively concentrated.

[0119] S43, judging whether there is outlier data according to the discreteness analysis result;

[0120] Specifically, outlier data refers to data points that are significantly different from most data points in a data set. They may be caused by errors, abnormal events, or other reasons. According to the discreteness analysis results of secondary data, a reasonable threshold (such as a certain multiple of the standard deviation) is set. When a data point exceeds this threshold, it is considered to be an outlier.

[0121] S44, if there is no outlier data, marking the secondary data as normal data;

[0122] Specifically, if there is no outlier data in the secondary data, it means that the overall performance of the current vibration data is normal, and these secondary data can be marked as normal data. No additional analysis and processing is required for the normal data.

[0123] S45. If outlier data exists, trace the source of the outlier data and mark the corresponding intrusion device as the first outlier device.

[0124] Specifically, if there are outlier data in the secondary data, it is necessary to trace the source of these outlier data. This usually involves checking the intrusion devices that collected the data one by one. Once the source of the outlier data is determined, the corresponding intrusion device is marked as the "first outlier device". This helps to further inspect, repair or replace the device in the future to reduce false positives or false negatives.

[0125] Optionally, if outlier data exists, tracing back the source of the outlier data and marking the corresponding intrusion device as the first outlier device further includes:

[0126] S451. Acquire, according to the first outlier device, at least one second outlier device associated with the first outlier device;

[0127] Specifically, after the first outlier device is identified, the correlation between the device and other intrusion devices needs to be analyzed. This includes examining the physical connection, signal transmission, data interaction, etc. between them. Based on the correlation analysis, other intrusion devices that are directly or indirectly associated with the first outlier device are identified and marked as "second outlier devices". These associations may be due to factors such as common signal sources, close geographical locations, and similar operating environments.

[0128] S452: Analyze the cause of the outlier data according to the operation data of the second outlier device and the first outlier device.

[0129] Specifically, detailed operating data is collected from the first outlier device and the second outlier device, including but not limited to vibration data, temperature, humidity, current, voltage and other factors that may affect the performance of the device. The collected data is compared with the data during normal operation to find differences and anomalies. This helps to determine whether the outlier data is caused by a failure of the device itself, interference from the external environment, problems with signal transmission, etc. Combined with the operating principle of the device, historical fault records, maintenance records and other information, the outlier data is comprehensively analyzed. Through methods such as elimination and cause-and-effect analysis, the scope of the causes of the outlier data is gradually narrowed down, and the most likely cause is finally determined.

[0130] S50, obtaining intrusion detection analysis results according to the abnormal data;

[0131] Optionally, the step of obtaining an intrusion detection analysis result according to the abnormal data further includes:

[0132] S511 , obtaining first abnormal data in the vibration data that is smaller than the preset vibration range, and tracing the source of the first abnormal data.

[0133] Specifically, first abnormal data with a vibration smaller than a preset vibration range (ie, lower than a normal threshold) is screened out from the vibration data. This situation may indicate that the intrusion collection device is faulty, has reduced sensitivity, or is subject to external interference.

[0134] S512: If the first abnormal data source is located in an isolated first intrusion collection device, mark the first intrusion collection device and output a first fault alarm.

[0135] Specifically, the first abnormal data is traced back to determine its source. If the source is an isolated first intrusion collection device, that is, the device has no direct association or adjacent relationship with other devices, the next step is carried out. The faulty first intrusion collection device is marked for subsequent maintenance or replacement. At the same time, the first fault alarm is output to notify relevant personnel to conduct inspection and repair.

[0136] S513: If the first abnormal data comes from multiple consecutive second intrusion collection devices, mark the fence where the second intrusion collection device is located and output a second fault alarm.

[0137] Specifically, if the first abnormal data comes from multiple consecutive second intrusion collection devices, that is, these devices are geographically adjacent or belong to the same fence area, the next step of processing is performed. The fence where the faulty second intrusion collection device is located is marked for subsequent inspection and maintenance. At the same time, a second fault alarm is output to notify relevant personnel to inspect the fence to prevent security vulnerabilities caused by fence failure. At this time, the possible failure of the fence is that obstacles (such as branches) squeeze the fence, or the fence collapses, causing the fence to fail to vibrate normally.

[0138] Optionally, the step of obtaining an intrusion detection analysis result according to the abnormal data further includes:

[0139] S521 , obtaining second abnormal data in the vibration data that is greater than the preset vibration range, and tracing the source of the second abnormal data.

[0140] Specifically, second abnormal data with a vibration greater than a preset range (ie, higher than a normal threshold) is screened out from the vibration data. This may indicate that an intrusion has occurred, or that the intrusion collection device has been subjected to external impact or false triggering.

[0141] S522: If the abnormal data originates from an isolated third intrusion collection device, a first intrusion alarm is output.

[0142] Specifically, the second abnormal data is traced back to determine its source. If the source is an isolated third intrusion collection device, that is, the device has no direct association or adjacent relationship with other devices, the next step is carried out. If the second abnormal data comes from an isolated third intrusion collection device, and further analysis confirms that there is an intrusion behavior (such as through cross-verification with other sensor data), the first intrusion alarm is output and the relevant personnel are notified to handle it.

[0143] S523: If the abnormal data comes from a plurality of consecutive fourth intrusion collection devices, obtain image information of the area where the fourth intrusion collection devices are located.

[0144] Specifically, if the second abnormal data originates from multiple consecutive fourth intrusion collection devices, that is, these devices are geographically adjacent or belong to the same area, the next step of processing is performed. The video surveillance system or other image acquisition device associated with the area is called to obtain real-time image information of the area where the fourth intrusion collection device is located. The image information can be real-time video, photos, or thermal images. The image information can be obtained by the first sensor unit on the intrusion detection device, or by real-time acquisition of image information by satellite.

[0145] S524. Based on the image information, output a second intrusion alarm or a third fault alarm indicating that a fence where the fourth intrusion collection device is located is faulty.

[0146] Specifically, the image information is analyzed, and if an intrusion is confirmed, a second intrusion alarm is output to notify relevant personnel to respond immediately. If the image information shows that the fence where the fourth intrusion collection device is located is damaged, collapsed or otherwise faulty, a third fault alarm indicating that the fence where the fourth intrusion collection device is located is faulty is output to notify relevant personnel to conduct maintenance.

[0147] Optionally, the step of outputting a second intrusion alarm or a third fault alarm of a fence failure where the fourth intrusion collection device is located based on the image information includes:

[0148] S5241, preprocessing the image information to obtain a target image;

[0149] Specifically, the acquired image information is preprocessed, including denoising, contrast enhancement, cropping irrelevant areas, etc., to obtain a clear, high-quality target image.

[0150] S5242. Extract key features based on the target image.

[0151] Specifically, image processing algorithms, such as edge detection, morphological operations, feature point extraction, etc., are used to extract key features, such as the shape, contour, texture, etc. of the object, from the target image.

[0152] S5243. Identify the object or behavior in the target image according to the key features, and output the identification result.

[0153] Specifically, machine learning or deep learning models, such as convolutional neural networks (CNNs) and support vector machines (SVMs), are applied to classify and identify the extracted key features to determine the objects or behaviors in the target image.

[0154] S5244. Determine whether there is an intrusion or a fence failure based on the recognition result.

[0155] Specifically, the identified object or behavior is matched with a preset intrusion behavior pattern or fence failure pattern to determine whether there is an intrusion behavior or a fence failure.

[0156] S5245: If an intrusion is identified, a second intrusion alarm is output.

[0157] Specifically, if the identification result confirms that there is an intrusion behavior, a second intrusion alarm is immediately output to notify relevant personnel to handle it.

[0158] S5246: If a fence failure is identified, a third fault alarm indicating that the fence where the fourth intrusion collection device is located is faulty is output.

[0159] Specifically, if the recognition result confirms that there is a fence fault, such as fence damage, collapse, etc., then the third fault alarm of the fence fault where the fourth intrusion collection device is located is output, and the relevant personnel are notified to carry out maintenance. Through the above operation steps, we can more accurately use image information to assist intrusion identification and fence fault detection, and improve the accuracy and reliability of the system. At the same time, through timely alarm output, we can ensure that relevant personnel can respond quickly and effectively deal with intrusion behaviors and fence failures.

[0160] For ease of understanding, let's assume that in a security monitoring system, one hundred intrusion collection devices are deployed, evenly distributed on the fence around a large warehouse to monitor potential intrusions. The system's preset vibration range is ten to one hundred units, and any data exceeding or below this range is considered abnormal.

[0161] When the system detects at a certain moment that the vibration data returned by the No. 5 intrusion collection device (isolated device) is five units, which is lower than the minimum value of ten units in the preset range.

[0162] According to step S511, the system obtains the first abnormal data which is smaller than the preset vibration range, and traces its source to the fifth intrusion collection device.

[0163] Since device No. 5 is isolated (ie, no other adjacent intrusion collection devices around it report similar anomalies), the system marks the device according to step S512 and outputs a first fault alarm to notify maintenance personnel to check whether the device has a fault or sensitivity problem.

[0164] Second abnormal data processing:

[0165] Subsequently, the system detected that the vibration data sent back by the consecutive intrusion collection devices No. 10 to 15 (a total of 6 consecutive devices) all exceeded one hundred units, which was higher than the maximum value of the preset range.

[0166] According to step S521, the system obtains the second abnormal data that is greater than the preset vibration range, and traces its source to the six consecutive intrusion collection devices.

[0167] Since these abnormal data come from multiple continuous devices, the system triggers the image information acquisition process according to step S523, calls the video monitoring system associated with the area where these devices are located, and obtains real-time image information.

[0168] In steps S5241 to S5243, the system preprocesses the image information, extracts key features, and identifies objects or behaviors in the image.

[0169] Assuming that an unknown person is identified in the image as trying to climb the fence, the system determines that there is an intrusion according to step S5244, and outputs a second intrusion alarm according to step S5245, notifying the security personnel to respond immediately.

[0170] If what is identified in step S5243 is not an intrusion but a part of the fence is damaged or collapsed, the system outputs a third fault alarm of the fence where the fourth intrusion collection device is located according to step S5246, and notifies the maintenance personnel to repair the fence as soon as possible to prevent potential security loopholes.

[0171] Example 6

[0172] This embodiment provides a mounting structure for mounting an intrusion detection device on a fence. Figure 5-Figure 7 .

[0173] In this embodiment, a hook is provided on one side of the fence 400, and a hanging hole for the hook to cooperate is provided on the other side of the fence 400. The hooks and hooks of adjacent fences 400 are connected by cooperation, and several fences 400 are connected and spliced ​​in sequence to form a circular enclosure. The intrusion detection device 100 is installed on the fence 400. Depending on the size of the enclosure, it may be necessary to install the intrusion detection device 100 at different positions of the fence 400, or increase or decrease the intrusion detection device 100 according to actual usage requirements. Therefore, a connection component is provided on the intrusion detection device 100, and the intrusion detection component 100 can be quickly disassembled and installed on the fence 400 through the connection component.

[0174] The intrusion detection device 100 is arranged on the fence 400 through a connection assembly, and the fence 400 has a plurality of meshes. The connection assembly includes a connection member 110 and at least two hook units 130;

[0175] The connecting member 110 has a positioning portion, the intrusion detection device 100 is arranged at the positioning portion, at least two hook units 130 are arranged on the side wall of the connecting member 110, the hook unit 130 includes a pull rod 120 protruding from the side wall of the connecting member 110, and one end of the pull rod 120 away from the connecting member 110 is bent to form a bent portion 121, and the bent portion 121 can enter the mesh;

[0176] The bending portions 121 of at least two hook units 130 can move in a direction close to or away from the connecting piece 110 , so that at least two limiting portions can respectively form limiting structures with the inner wall of the mesh to achieve the connection between the connecting piece 110 and the fence 400 .

[0177] Specifically, by setting the connection assembly, the intrusion detection device 100 can be first installed on the connection assembly, and then quickly installed on the fence 400 through the connection assembly. The hook units 130 can be provided with two, three or four. When the number of the hook units 130 is only two, the two hook units 130 are arranged opposite to each other. When the number of the hook units 130 is three or four, they are respectively arranged on the four sides of the connecting member 110. Figure 7 What is shown is a schematic diagram of three hook units 130. A bending portion 121 is provided at the end of the pull rod 120, and by providing the bending portion 121, the bending portion 121 can enter into the mesh of the fence 400. Each pull rod 120 unit has a bending portion 121, and each bending portion 121 enters into a mesh, and the bending portion 121 can move in a direction close to or away from the connecting member 110, so that the bending portion 121 can form a limiting structure with the inner wall of the mesh, and all the bending portions 121 cooperate to achieve the gripping of the fence 400, thereby achieving the connection between the connecting member 110 and the fence 400. The integrity of the intrusion detection device 100 and the fence 400 is improved, and the data of the fence 400 when vibrating can be obtained more accurately. The bending portion 121 can move so as to be applicable to fences 400 with different mesh sizes, thereby improving versatility. Since the bent portion 121 of the hook unit 130 is gradually inserted into the mesh, no damage is caused to the fence 400 , thereby protecting the integrity of the fence 400 .

[0178] Optionally, at least two elastic abutment units 150 are disposed on the periphery of the positioning portion of the connecting member 110 , and the elastic abutment unit 150 includes a positioning plate 151 and an elastic plate 152 ;

[0179] One end of the positioning plate 151 is connected to the side wall of the connecting member 110, and the other end is a free end. The first end of the elastic plate 152 is connected to the free end of the positioning plate 151, and the second end of the elastic plate 152 is arc-shaped and bent toward the direction close to the positioning portion. All the elastic plates 152 cooperate to form a accommodating space for accommodating the intrusion detection device 100.

[0180] Specifically, two or four elastic abutment units 150 are arranged on the periphery of the positioning portion. When the number of the elastic abutment units 150 is two, the two elastic abutment units 150 are arranged opposite to each other. When the number of the elastic abutment units 150 is four, the four elastic abutment units 150 are arranged on four sides respectively. All the elastic abutment units 150 enclose to form a containing space for limiting the intrusion detection device 100. In the process of installing the intrusion detection device 100 on the connecting member 110, the intrusion detection device 100 squeezes the elastic plate 152, causing the elastic plate 152 to undergo elastic deformation, and all the elastic plates 152 cooperate to clamp the intrusion detection device 100, thereby achieving a stable connection and ensuring that the intrusion detection device 100 will not fall off during operation.

[0181] Optionally, the hook unit 130 includes a connecting rod 131, a guide rod 132, a guide block 133 and a compression spring 134;

[0182] The connecting member 110 is provided with a receiving chamber 111 inside, the guide block 133 is provided in the receiving chamber 111, the side wall of the connecting member 110 is provided with a connecting groove 112, a connecting hole connecting the connecting groove 112 and the receiving chamber 111, the inner diameter of the connecting hole is smaller than the inner diameter of the connecting groove 112, the connecting rod 131 is at least partially provided in the connecting groove 112, the connecting rod 131 has a threaded hole threadedly matched with the pull rod 120, the guide rod 132 passes through the connecting hole, the two ends of the guide rod 132 are respectively connected to the connecting rod 131 and the guide block 133, and the compression spring 134 is provided between the guide block 133 and the inner wall of the receiving chamber 111;

[0183] A driving block 140 is also disposed in the accommodating cavity 111 . The driving block 140 is located on the same side of all the guide blocks 133 . The driving block 140 has a conical driving surface 141 .

[0184] Each guide block 133 has a guide slope 142 for cooperating with the driving surface 141 . The driving block 140 moves in a direction close to the guide block 133 , and the driving surface 141 contacts the guide slope 142 to drive all the bending portions 121 to move in a direction away from the connecting member 110 .

[0185] Specifically, the connecting rod 131, the pull rod 120, the guide rod 132 and the guide block 133 constitute a whole hook, and the connecting groove plays a role of limiting and guiding the movement of the connecting rod 131, and the connecting hole plays a role of limiting and guiding the movement of the guide rod 132. A threaded hole is provided at one end of the connecting rod 131 away from the guide block 133, and the outer wall of the pull rod 120 has an external thread that matches the threaded hole. Through the threaded cooperation between the pull rod 120 and the connecting rod 131, the length of the whole hook can be adjusted. By adjusting the overall length of the hook, the distance between the bent portion 121 at the upper end or the left and right ends (the orientation is relative to the connecting member 110) can be adjusted. When the mesh is a square hole, the distance between the bent portion 121 and the connecting member 110 is equal. When the mesh is a diamond hole, the distance between the bent portion 121 at the left and right ends and the connecting member 110 is equal, and the distance between the bent portion 121 at the upper end and the connecting member 110 is adaptively adjusted according to the size of the diamond hole. In this way, the fence 400 with different mesh shapes can be adapted to ensure that the connecting member 110 can be adapted, thereby improving the adaptation range of the connecting assembly.

[0186] By providing the compression spring 134, the bending portion 121 always has a tendency to move toward the direction close to the connecting member 110, that is, the bending portions 121 located at the upper end, left end and right end of the connecting member 110 all have a pulling force to move toward the connecting member 110, and the bending portions 121 in three directions form a limiting structure with the inner walls of the three meshes, and the three bending portions 121 cooperate with each other to achieve the grip of the fence 400. In order to improve the position stability of the compression spring 134, a spring groove can be provided on the inner wall of the accommodating cavity 111, and a part of the compression spring 134 is located in the spring groove, and the spring groove plays a limiting role on the compression spring 134.

[0187] Before installing the connecting member 110 to the fence 400, the movement of the driving block 140 is controlled so that the driving surface 141 on the driving block 140 contacts the guiding inclined surface 142 of the guiding block 133. The driving surface 141 applies a component force coincident with the axis of the guiding rod 132 to the guiding block 133, so that all the bending portions 121 move outward, thereby increasing the distance between all the bending portions 121 and the connecting member 110; then each bending portion 121 is placed in a corresponding mesh respectively, and then the driving block 140 is moved in the reverse direction. The guiding block 133 loses the external force of the driving block 140 and automatically moves toward the direction close to the connecting member 110 under the action of the compression spring 134. All the bending portions 121 move inward to grasp the fence 400, thereby achieving the installation of the connecting member 110 on the fence 400.

[0188] It should be noted that a driving rod can be connected to the driving block 140, and the driving rod passes through the side wall of the connecting piece 110, so that an external force for moving the driving block 140 can be applied through the driving rod. In order to prevent an intruder from controlling the driving block 140, the driving rod can be set as an anti-theft component, and the driving rod can be detachably connected to the driving block 140; further, a limiting groove can be set in the accommodating groove, and the driving block 140 also has a limiting surface with an equal outer diameter, and the outer diameter of the limiting surface is equal to the maximum outer diameter of the guiding inclined surface 142, and the outer diameter of the limiting surface matches the inner diameter of the limiting groove, that is, the limiting groove and the limiting surface cooperate to achieve a limiting and guiding role for the moving path of the driving block 140, to ensure that during the reciprocating movement of the driving block 140, the driving surface 141 can always abut against the guiding inclined surface 142 of the driving block 140.

[0189] When the connector 110 needs to be removed from the fence 400, the above operation can be reversed. The connector 110 can be quickly installed and removed through the hook unit 130, and the relative position of the connector 110 on the fence 400 can be quickly adjusted according to needs, thereby improving the efficiency of installation and removal and ensuring the stability of the connector 110 after installation.

[0190] Example 7

[0191] Furthermore, this embodiment provides an intrusion identification device based on meteorological monitoring, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the above-mentioned intrusion identification methods based on meteorological monitoring.

[0192] Example 8

[0193] Furthermore, this embodiment provides a computer-readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement any of the above methods.

[0194] In some embodiments, the computer readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or various devices including one or any combination of the above memories. The computer may be various computing devices including intelligent terminals and servers.

[0195] In the above embodiments of the present disclosure, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0196] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0197] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0198] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0199] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present disclosure is essentially 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, and the computer software product is stored in a non-volatile storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0200] The above is only a preferred embodiment of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present disclosure. These improvements and modifications should also be regarded as the scope of protection of the present disclosure.

Claims

1. An intrusion identification system based on meteorological monitoring, characterized in that: include: A fence, an intrusion detection device arranged on the fence, and also a meteorological sensor system and an edge control unit matched with the fence, wherein the intrusion detection device and the meteorological sensor system are connected to the edge control unit; The intrusion detection device is used to collect vibration data on the fence and send the vibration data to the edge control unit; The meteorological sensor system is used to collect meteorological data of the area where the fence is located, and send the meteorological data to the edge control unit; The edge control unit corrects the vibration data according to the received meteorological data, and completes the intrusion detection analysis according to the corrected vibration data.

2. The intrusion identification system based on meteorological monitoring according to claim 1 is characterized in that: The intrusion detection device comprises a first sensing unit for collecting image data and first vibration data and / or a second sensing unit for collecting second vibration data; the distance between two adjacent first sensing units is l≤L1; The number of the second sensing units arranged between two adjacent first sensing units is n, and n satisfies (n+1)L2≥L1, where L1 is the image acquisition limit, L2 is the vibration acquisition limit, and n is a natural number.

3. An intrusion identification method based on meteorological monitoring, characterized in that: The following steps are involved: Acquire historical vibration data collected by the intrusion device, and train a learning model based on the historical vibration data and corresponding historical meteorological data; Obtain vibration data collected by the intrusion device and meteorological data collected by the meteorological sensor system; Obtaining a preset vibration range according to the meteorological data and the trained learning model; Comparing the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range; An intrusion detection analysis result is obtained based on the abnormal data.

4. The intrusion identification method based on meteorological monitoring according to claim 3 is characterized in that: The step of obtaining a preset vibration range according to the meteorological data and the trained learning model comprises: Obtain wind direction information and wind speed information according to the meteorological data; According to the wind direction information, define the part of the fence whose extension direction is perpendicular to the wind direction as the windward fence, mark at least one intrusion device on the windward fence as the windward intrusion device, define the part of the fence whose extension direction is parallel to the wind direction as the downwind fence, mark at least one intrusion device on the downwind fence as the downwind intrusion device; According to the wind direction information, the wind speed information and the learning model, the preset vibration ranges for collecting vibration data of the headwind intrusion device and the downwind intrusion device are respectively obtained.

5. The intrusion identification method based on meteorological monitoring according to claim 3 is characterized in that: The step of comparing the vibration data with the preset vibration range to obtain abnormal data in the vibration data that is outside the preset vibration range also includes: Comparing the vibration data with the preset vibration range to obtain secondary data in the vibration data that is within the preset vibration range; According to the secondary data, calculating the standard deviation of the secondary data and evaluating its dispersion; According to the discreteness analysis result, determining whether there is outlier data; If not, marking the secondary data as normal data; If so, the source of the outlier data is traced back and the corresponding intrusion device is marked as the first outlier device.

6. The intrusion identification method based on meteorological monitoring according to claim 5 is characterized in that: If yes, tracing back the source of the outlier data and marking the corresponding intrusion device as the first outlier device also includes: According to the first outlier device, obtaining at least one second outlier device associated with the first outlier device; The cause of the outlier data is analyzed based on the operation data of the second outlier device and the first outlier device.

7. The intrusion identification method based on meteorological monitoring according to claim 3 is characterized in that: The step of obtaining the intrusion detection analysis result according to the abnormal data further includes: Acquire first abnormal data in the vibration data that is smaller than the preset vibration range, and trace the source of the first abnormal data; If the first abnormal data source is located in an isolated first intrusion collection device, marking the first intrusion collection device and outputting a first fault alarm; If the first abnormal data comes from multiple consecutive second intrusion collection devices, the fence where the second intrusion collection device is located is marked and a second fault alarm is output.

8. The intrusion identification method based on meteorological monitoring according to claim 3 is characterized in that: The step of obtaining the intrusion detection analysis result according to the abnormal data further includes: Acquire second abnormal data in the vibration data that is greater than the preset vibration range, and trace the source of the second abnormal data; If the abnormal data originates from an isolated third intrusion collection device, outputting a first intrusion alarm; If the abnormal data is from a plurality of consecutive fourth intrusion collection devices, acquiring image information of the area where the fourth intrusion collection device is located; Based on the image information, a second intrusion alarm or a third fault alarm indicating that a fence where the fourth intrusion collection device is located is faulty is output.

9. The intrusion identification method based on meteorological monitoring according to claim 8 is characterized in that: The step of outputting a second intrusion alarm or a third fault alarm of a fence failure where the fourth intrusion collection device is located based on the image information comprises: Preprocessing the image information to obtain a target image; Extracting key features according to the target image; According to the key features, identify the object or behavior in the target image and output the recognition result; Based on the recognition results, determine whether there is intrusion or fence failure; If an intrusion behavior is identified, a second intrusion alarm is output; If a fence failure is identified, a third failure alarm indicating that the fence where the fourth intrusion collection device is located is faulty is output.

10. An intrusion identification device based on meteorological monitoring, characterized in that: The intrusion identification device based on meteorological monitoring includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the intrusion identification method based on meteorological monitoring according to any one of claims 6-9.

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