Railway surrounding intrusion monitoring and warning system

Abstract

The invention relates to a railway intrusion monitoring and warning system which integrates a data acquisition module, an edge calculation module, a data transmission module, a cloud processing module and a user interaction module and realizes real-time monitoring of the environment along a railway. Through the camera and the millimeter-wave radar, the system acquires video and radar data, and through intelligent analysis of the edge calculation module, potential intruders are quickly identified and alarm is triggered. And the data is uploaded to the cloud through the transmission module, and alarm information is pushed to a user after secondary judgment by the cloud processing module. The user interaction module provides a visual interface, so that an administrator can check alarms and equipment states conveniently, and meanwhile, interaction between a user and the system is supported. The system has the advantages of being high in real-time performance, high in intelligent degree and capable of rapidly responding and effectively preventing railway intrusion events and improving railway operation safety. Meanwhile, cloud processing is combined with the user interaction module, so that the system is more flexible and easy to manage.

Description

Technical Field

[0001] The invention relates to the field of railway and information interaction, in particular to an intrusion monitoring system around railways. Background Art

[0002] With the rapid development of railway transportation, railway safety has become a vital issue. Traditional railway safety monitoring methods mainly rely on manual patrols and video surveillance, but these methods have limitations such as high labor costs, many monitoring blind spots, and slow response speed. Especially in the complex and changeable environment along the railway, potential intruders such as people, animals, and vehicles may appear at any time, which poses a great hidden danger to railway operation safety. Summary of the invention

[0003] In view of the above situation, it is necessary to provide a railway perimeter intrusion monitoring and alarm system that solves at least one of the above problems, including:

[0004] The data acquisition module is used to collect video and radar data along the railway through cameras and millimeter-wave radar equipment to monitor the railway environment in real time;

[0005] The edge computing module is connected to the data acquisition module to analyze the collected video and radar data in real time, identify potential intruders such as people, animals, and vehicles through intelligent algorithms, and trigger corresponding alarms;

[0006] A data transmission module, connected to the edge computing module, for transmitting data processed by the edge computing module to the cloud platform;

[0007] The cloud processing module is connected to the data transmission module, and is used to receive data from the data transmission module, perform secondary judgment and processing, and push the alarm information to the corresponding user;

[0008] The user interaction module is connected to the cloud processing module to provide a user interface and allow administrators to view alarm information and device status, and support interactive operations between users and the system.

[0009] Preferably, after identifying a potential intruder, if the edge computing module detects that the intruder's movement speed exceeds 5 meters per second, and its movement direction is pointing towards the railway track, and the closest distance to the railway track is less than 50 meters, it will be judged as an intrusion through a preset algorithm and an alarm will be triggered.

[0010] Preferably, after receiving the data from the data transmission module, the cloud processing module will verify the timestamp and integrity check code of the data. If the timestamp differs from the current time by more than 5 minutes, or the integrity check code does not match, the data is judged to be incomplete or abnormal, a data error alarm is triggered, and a data retransmission mechanism is started.

[0011] Preferably, the user interaction module allows the administrator to customize the alarm trigger conditions, including but not limited to setting the intruder's moving speed threshold to 3 meters per second, the moving direction range to an angle less than 30 degrees with the railway track, and the safety distance threshold from the railway track to 100 meters. When these conditions are met, an alarm is triggered.

[0012] Preferably, the intelligent learning module automatically adjusts the logical judgment conditions for alarm triggering by analyzing historical data.

[0013] Preferably, the intelligent learning module incorporates the influence of geographical location on the behavior of intruders, increases the monitoring sensitivity value for animal intrusions in mountainous areas or near wildlife reserves, and reduces the speed threshold for triggering an alarm.

[0014] Preferably, the alarm level management module divides the alarm information into three levels according to the urgency of the alarm information and the size of the potential risk: level one alarm, level two alarm and level three alarm, wherein the triggering conditions of the level one alarm include that the intruder moves at a speed exceeding 5 meters per second and is less than 50 meters from the railway track; the triggering conditions of the level two alarm include that the intruder moves at a speed exceeding 3 meters per second and is less than 100 meters from the railway track; other situations trigger the level three alarm.

[0015] Preferably, the alarm level management module will also include intruder type analysis when classifying alarm levels, and directly trigger a level one alarm when a vehicle intrusion is detected.

[0016] Preferably, the alarm history record module will store detailed information of each alarm, including alarm time, longitude and latitude coordinates, intruder type, alarm level, processing result, and name and processing time of the processing personnel.

[0017] Preferably, the alarm history recording module also supports visual analysis of alarm data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a railway perimeter intrusion monitoring system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clear, the following is a further detailed description of the railway perimeter intrusion monitoring system of the present invention in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0020] In the description of the present invention, unless otherwise specified, "multiple" means two or more; the terms "center", "longitudinal", "lateral", "up", "down", "left", "right", "inside", "outside", "front end", "rear end", "head", "tail", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third" and the like are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0021] In the description of this utility, it should be noted that, unless otherwise clearly specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it 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 it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this utility can be understood by specific circumstances.

[0022] See also Figure 1 The railway intrusion monitoring and alarm system of the embodiment of the present invention includes: a data acquisition module, which is used to collect videos and radar data along the railway through cameras and millimeter-wave radar equipment, and monitor the railway environment in real time; an edge computing module, which is connected to the data acquisition module, is used to analyze the collected video and radar data in real time, identify potential intruders such as people, animals, and vehicles through intelligent algorithms, and trigger corresponding alarms; a data transmission module, which is connected to the edge computing module, is used to transmit the data processed by the edge computing module to the cloud platform; a cloud processing module, which is connected to the data transmission module, is used to receive data from the data transmission module, perform secondary judgment and processing, and push the alarm information to the corresponding user; a user interaction module, which is connected to the cloud processing module, is used to provide a user interface and administrators to view alarm information and equipment status, and support interactive operations between users and the system.

[0023] In the above embodiment, the data acquisition module is the front-end part of the system, which is mainly responsible for collecting video and radar data along the railway through cameras and millimeter-wave radar devices. The camera can capture video images around the railway and provide intuitive environmental information; while the millimeter-wave radar device can detect objects around the railway, which is not affected by light and weather, and provides more stable detection data. The working principle of the data acquisition module is to automatically or manually control the camera and radar device to collect data through preset acquisition parameters and strategies. The camera captures images through the lens, and after photoelectric conversion and digital processing, a video data stream is formed; the radar device calculates the distance, speed and direction of the target object by emitting millimeter waves and receiving echo signals to form a radar data stream. After preliminary processing, these two data streams are transmitted to the edge computing module for further analysis and processing. The edge computing module is the core part of the system and is responsible for real-time analysis of the collected video and radar data. The module uses intelligent algorithms to detect, track and identify video images, and can accurately identify potential intruders such as people, animals, and vehicles; at the same time, the radar data is parsed and fused to improve the accuracy and reliability of target recognition and tracking. The working principle of the edge computing module is based on a high-performance computing platform and advanced algorithm technology. It first receives the video and radar data streams from the data acquisition module, and then uses the target detection algorithm to analyze the video image frame by frame to identify the target object in the image; then, it uses the target tracking algorithm to continuously track the target object to obtain its motion trajectory and speed and other information; finally, it combines the radar data to identify and classify the target object to determine whether it is a potential intruder. If it is determined to be an intruder, the corresponding alarm signal is triggered and the alarm information is transmitted to the data transmission module. The data transmission module is responsible for transmitting the data processed by the edge computing module to the cloud platform. Due to the complex and changeable environment along the railway, the stability and reliability of data transmission are crucial to the performance of the system. Therefore, the data transmission module adopts an efficient data transmission protocol and encryption algorithm to ensure the security and real-time performance of data during transmission. The working principle of the data transmission module is to establish a stable data transmission channel to transmit the alarm information and related data streams generated by the edge computing module to the cloud platform. During the transmission process, the data transmission module will compress and encrypt the data to reduce the occupancy of the transmission bandwidth and prevent the risk of data leakage. At the same time, the data transmission module also has breakpoint resumption and retransmission mechanisms to ensure the integrity and reliability of data during transmission. The cloud processing module is the back-end part of the system, responsible for receiving data from the data transmission module, making secondary judgments and processing, and pushing alarm information to the corresponding users. This module uses cloud computing technology, has powerful computing and storage capabilities, and can efficiently process and analyze massive amounts of data.The working principle of the cloud processing module is to first receive the data stream from the data transmission module, and then use big data analysis technology to mine and analyze the data to extract valuable information and patterns. Then, the alarm information is judged and processed again according to the preset rules and algorithms to improve the accuracy and reliability of the alarm. Finally, the processed alarm information is pushed to the corresponding user through the user interaction module for the administrator to view and process. The user interaction module is the human-computer interaction part of the system, which is responsible for providing the user interface and the administrator to view the alarm information and equipment status, and supports the interaction between the user and the system. This module provides users with convenient operation experience and rich functional support through a graphical interface and friendly interactive design. The working principle of the user interaction module is to realize the interaction between the user and the system by establishing a communication channel between the user and the system. The administrator can view key information such as real-time video, alarm information, equipment status, etc. through the user interface; at the same time, the system can also be configured with parameters, equipment control, etc. through the user interface. In addition, the user interaction module also supports a variety of interaction methods, such as touch screen, mouse and keyboard, etc., to meet the needs and habits of different users. Through the cooperation of five parts, namely data acquisition module, edge computing module, data transmission module, cloud processing module and user interaction module, the real-time monitoring and alarm function of the railway environment is realized. The system not only has the advantages of high efficiency, intelligence and reliability, but also can provide users with rich functional support and convenient operation experience.

[0024] See also Figure 1 In another embodiment, after the edge computing module identifies a potential intruder, if it is detected that the intruder's moving speed exceeds 5 meters per second, and its moving direction is pointing to the railway track, and the closest distance to the railway track is less than 50 meters, it will be judged as an intrusion through a preset algorithm and an alarm will be triggered.

[0025] In the above embodiment, the working principle of the edge computing module in the railway intrusion monitoring and alarm system mainly involves multiple steps such as real-time data collection, target detection and tracking, verification of intrusion judgment conditions, and confirmation and triggering of alarm information. The module first receives the video and radar data from the data acquisition module. After preprocessing, it uses the pre-trained algorithm model to detect the target of the video image and identify the targets such as people, animals, and vehicles in the image. Once the target is detected, the module will start the target tracking algorithm to obtain information such as the target's motion trajectory and speed. After obtaining the target's motion information, the edge computing module will make a decision based on the preset intrusion judgment conditions. These conditions usually include the target's moving speed, moving direction, and the closest distance to the railway track. If the target's moving speed is detected to exceed 5 meters per second, and its moving direction points to the railway track, and the closest distance to the railway track is less than 50 meters, the module will judge the target as a potential intruder. In order to ensure the accuracy and reliability of the alarm, the edge computing module will further confirm the potential intruder through a preset algorithm. Once the target is confirmed to be an intruder, the module will immediately trigger an alarm signal and package the alarm information into a specific data format, which will be sent to the cloud processing module through the data transmission module for further processing and analysis. In the cloud, the alarm information may be correlated and analyzed with other data to provide a more comprehensive security situation awareness.

[0026] See also Figure 1 In another embodiment, after receiving the data from the data transmission module, the cloud processing module will verify the timestamp and integrity check code of the data. If the timestamp differs from the current time by more than 5 minutes, or the integrity check code does not match, the data is judged to be incomplete or abnormal, a data error alarm is triggered, and a data retransmission mechanism is started.

[0027] In the above embodiment, the cloud processing module receives data packets from the data transmission module. These data packets usually contain real-time information about potential intruders sent from the edge computing module, such as key data such as location, speed, and timestamp. Once the data arrives at the cloud, the processing module immediately starts the data verification process. The first step of data verification is timestamp verification. The timestamp is the key information in the data packet that records the time when the data is generated, which is essential to ensure the timeliness and accuracy of the data. The cloud processing module extracts the timestamp in the data packet and compares it with the current time. If the timestamp differs from the current time by more than 5 minutes, it means that the data may have serious delays or transmission errors, thereby affecting the real-time and validity of the data. In this case, the cloud processing module will determine that the data is incomplete or abnormal, and immediately trigger a data error alarm. At the same time as the alarm is triggered, the cloud processing module will also start the data retransmission mechanism. The purpose of this mechanism is to ensure the integrity and reliability of the data. When the cloud processing module detects that the data is abnormal, it will send a retransmission request to the data transmission module, requesting the data packet to be resent. After receiving the retransmission request, the data transmission module will repackage the data and send it to the cloud processing module. In this way, the cloud processing module can ensure the integrity and accuracy of the data and improve the reliability of the system. In addition to timestamp verification, the cloud processing module also matches the integrity check code. The integrity check code is an important tool for detecting whether the data has errors or has been tampered with during transmission. Before data transmission, the sender calculates the check code of the data and attaches it to the data packet. When the cloud processing module receives the data packet, it recalculates the check code of the data and compares it with the check code in the data packet. If the two match, it means that there is no error or tampering in the data transmission process; if they do not match, it means that there may be problems with the data. In the case of finding that the integrity check code does not match, the cloud processing module will also trigger a data error alarm and start the data retransmission mechanism. By retransmitting the data packet, the cloud processing module can ensure the integrity and accuracy of the data and avoid misjudgment or missed judgment due to data errors or tampering.

[0028] See also Figure 1 In another embodiment, the user interaction module allows the administrator to customize the alarm trigger conditions, including but not limited to setting the intruder's moving speed threshold to 3 meters per second, the moving direction range to an angle of less than 30 degrees with the railway track, and the safety distance threshold from the railway track to 100 meters. When these conditions are met, an alarm is triggered.

[0029] In the above embodiment, the user interaction module provides an intuitive and easy-to-use interface through which the administrator can access and manage the alarm trigger conditions of the system. This interface usually includes a series of editable parameters and options, which the administrator can set and adjust as needed. When customizing the alarm trigger conditions, the administrator can set multiple parameters, including but not limited to the threshold of the intruder's moving speed, the range of the moving direction, and the threshold of the safe distance from the railway track. For example, in this example, the administrator can set the moving speed threshold to 3 meters per second, which means that the system will consider triggering an alarm only when the intruder's moving speed exceeds this threshold. At the same time, the administrator can also set the moving direction range. In this example, the moving direction range is set to an angle of less than 30 degrees with the railway track. This means that the system will only regard the intruder as a potential threat if the intruder's moving direction points to or approaches the railway track. Finally, the administrator can also set the safe distance threshold from the railway track. In this example, the safe distance threshold is set to 100 meters. This means that only when the intruder's closest distance to the railway track is less than this threshold will the system regard it as a potential intruder and consider triggering an alarm. Once the administrator has set these alarm trigger conditions, the user interaction module will pass these conditions to the core processing module of the system. When the core processing module detects an event that meets these conditions, it will trigger the corresponding alarm according to the administrator's settings. The alarm can be in a variety of forms, including sound, light flash, SMS notification, email reminder, etc., to ensure that the administrator can be informed of potential intrusion events in a timely manner. In addition, the user interaction module also allows the administrator to view and modify the set alarm trigger conditions at any time. In this way, the administrator can flexibly adjust the system's alarm trigger conditions according to changes in actual conditions to meet different security needs.

[0030] See also Figure 1 In another embodiment, the intelligent learning module automatically adjusts the logical judgment conditions for alarm triggering by analyzing historical data.

[0031] In the above embodiment, the intelligent learning module collects and analyzes a large amount of historical data. These data may come from various alarm records, surveillance videos, radar data, etc. generated by the railway intrusion monitoring system in daily operation. Through in-depth analysis of these data, the intelligent learning module can gradually understand and master the laws and characteristics of railway intrusion events. In the process of analyzing historical data, the intelligent learning module pays special attention to those intrusion events that are falsely reported or missed. For false alarm events, the intelligent learning module will try to find out the cause of the false alarm, which may be a special situation in a specific scenario, or a parameter setting that is improper. For missed alarm events, the intelligent learning module will analyze why the system failed to detect the intrusion event in time, whether it is due to incomplete data collection, insufficient processing speed, or too strict setting of logical judgment conditions. After mastering these laws and characteristics, the intelligent learning module will begin to automatically adjust the logical judgment conditions of the alarm trigger. This adjustment process is based on deep learning and machine learning algorithms. Through continuous iteration and optimization, the alarm trigger conditions of the system are more in line with the actual situation, reducing the possibility of false alarms and missed alarms.

[0032] Specifically, the intelligent learning module may adjust the following parameters:

[0033] 1. Movement speed threshold: Based on the distribution of intruder movement speeds in historical data, the intelligent learning module can automatically adjust the movement speed threshold. For example, if historical data shows that most intruders move within a certain range, then this range can be set as the new movement speed threshold.

[0034] 2. Movement direction range: Similarly, the intelligent learning module can also automatically adjust the movement direction range based on the distribution of intruder movement directions in historical data. This ensures that the system only alerts intruders who are actually heading towards the railway track.

[0035] 3. Safety distance threshold: The adjustment of the safety distance threshold is also based on historical data. The intelligent learning module analyzes the actual distance of the intruder from the railway track in the historical data, as well as the relationship between these distances and the alarm trigger, and automatically adjusts the safety distance threshold.

[0036] In addition to the parameter adjustments in the above three aspects, the intelligent learning module can also optimize some other logical judgment conditions, such as increasing the recognition ability of specific scenarios or special situations, and improving the flexibility and adaptability of the system.

[0037] See also Figure 1 In another embodiment, the intelligent learning module incorporates the effect of geographic location on intruder behavior, increases the monitoring sensitivity value for animal intrusions in mountainous areas or near wildlife reserves, and reduces the speed threshold for triggering an alarm.

[0038] In the above embodiment, the intelligent learning module uses technologies such as geographic information system (GIS) to accurately identify the geographical location characteristics of different areas along the railway, such as mountainous areas, wildlife reserves, etc. These areas are often difficult to effectively respond to by traditional intrusion monitoring systems due to factors such as complex terrain and dense vegetation. However, the intelligent learning module can combine the characteristics of these areas to formulate more reasonable monitoring strategies. In mountainous areas or near wildlife reserves, the intelligent learning module will pay special attention to the risk of animal invasion. It uses deep learning and data analysis technology to analyze animal invasion events in historical data and grasp key information such as animal activity patterns, movement speeds, and movement paths. This information provides a valuable reference for the system, enabling the system to more accurately predict and identify potential animal invasion behaviors. Based on the understanding of animal invasion behaviors in these areas, the intelligent learning module will adjust the monitoring strategy accordingly. It will increase the monitoring sensitivity values ​​for these areas and improve the frequency and accuracy of data collection in order to more comprehensively grasp the activities in these areas. At the same time, it will also reduce the speed threshold for alarm triggering to ensure that an alarm can be quickly issued when an animal approaches the railway track, providing sufficient response time for railway staff. This working principle of the intelligent learning module not only improves the accuracy and reliability of the monitoring system, but also enhances its adaptability and flexibility. It can automatically adjust the monitoring strategy and alarm trigger conditions according to the characteristics of different regions to ensure that the system can play the best effect in various complex environments. In addition, the intelligent learning module also has the ability to learn and optimize in real time. It can continuously collect new monitoring data and update the animal invasion behavior pattern based on this data. At the same time, it will also fine-tune the alarm trigger conditions according to the actual alarm trigger situation to ensure the accuracy and reliability of the system.

[0039] See also Figure 1 In another embodiment, the alarm level management module divides the alarm information into three levels according to the urgency of the alarm information and the size of the potential risk: level one alarm, level two alarm and level three alarm, wherein the triggering condition of the level one alarm includes that the intruder moves at a speed exceeding 5 meters per second and is less than 50 meters from the railway track; the triggering condition of the level two alarm includes that the intruder moves at a speed exceeding 3 meters per second and is less than 100 meters from the railway track; other situations trigger the level three alarm.

[0040] In the above embodiment, the alarm information is accurately divided into different levels according to the urgency of the alarm information and the size of the potential risk, so that the railway staff can respond quickly and accurately. Specifically, the alarm level management module divides the alarm information into three levels: level 1 alarm, level 2 alarm and level 3 alarm, and each level has its specific trigger conditions and response strategies. The following is the detailed working principle of the alarm level management module: The working principle of the alarm level management module is first based on the in-depth analysis of the alarm information. The alarm information received by the system usually contains multiple key parameters such as the moving speed of the intruder, the distance from the railway track, the time and location of the intrusion. These parameters are important bases for evaluating the urgency of the alarm and the potential risks. After receiving the alarm information, the alarm level management module will immediately start the evaluation process. First, it will check the moving speed parameter in the alarm information. If the intruder's moving speed exceeds 5 meters per second, this is an obvious emergency signal, because the high-speed moving intruder may quickly approach the railway track, posing a serious threat to the train operation. At the same time, the module will also check the distance parameter between the intruder and the railway track. If the distance is less than 50 meters, the intruder is already very close to the railway track, which further increases the urgency of the alarm. When these two conditions are met at the same time, the alarm level management module will immediately trigger a level 1 alarm. A level 1 alarm means that railway staff need to take immediate action, which may include emergency parking, evacuating passengers, etc., to ensure the safety of the train and passengers. If the intruder's moving speed exceeds 3 meters per second but does not reach 5 meters per second, and is less than 100 meters away from the railway track, the alarm level management module will trigger a level 2 alarm. Although the level 2 alarm is not as urgent as the level 1 alarm, it also requires railway staff to pay great attention. Staff may need to take corresponding safety measures according to the actual situation, such as slowing down and strengthening observation, to ensure the safe passage of the train. Except for the above two situations, all other alarm information will be classified as level 3 alarms. Level 3 alarms may include intruders with slower moving speeds and intruders far away from the railway track. Although these alarms do not pose a direct threat, they still require attention and processing by railway staff. Staff can monitor the scene in real time through the video surveillance system and take corresponding measures according to the actual situation.

[0041] See also Figure 1 In another embodiment, the alarm level management module will also include intruder type analysis when dividing the alarm levels, and directly trigger a level 1 alarm when a vehicle intrusion is detected.

[0042] In the above embodiment, when the system detects a vehicle intrusion, the alarm level management module will immediately trigger a level one alarm. This is because a vehicle, as a fast-moving object, often poses a much higher potential risk than pedestrians or other types of intruders. The high-speed movement of the vehicle may cause it to collide with the train, posing a serious threat to the safety of the train and passengers. When the level one alarm is triggered, the alarm level management module will quickly send the alarm information to the relevant staff and provide detailed alarm levels and response strategies. At the same time, the system will automatically initiate relevant safety measures, such as emergency parking, passenger evacuation, etc., to ensure the safety of the train and passengers.

[0043] See also Figure 1 In another embodiment, the alarm history record module will store detailed information of each alarm, including alarm time, longitude and latitude coordinates, intruder type, alarm level, processing result, and the name and processing time of the processing personnel.

[0044] In the above embodiment, the alarm history record module records various aspects of each alarm in detail. First, the alarm time is a very important parameter, which indicates the specific time point when the alarm occurs, which helps managers understand the frequency and trend of the alarm. Secondly, the latitude and longitude coordinates are the accurate identification of the alarm location. Through this information, the specific location where the alarm occurs can be quickly located, which is of great significance for on-site processing and subsequent investigation. The type of intruder is another key information, which reveals the source of the alarm. Whether it is pedestrians, vehicles or wild animals, different types of intruders may pose different degrees of threat to railway safety. By recording the type of intruder, managers can understand which areas or time periods are more prone to specific types of intrusions, so as to take corresponding preventive measures. The alarm level is another important field in the alarm history record module. It reflects the urgency of the alarm and the size of the potential risk. As mentioned above, the alarm level management module divides the alarm information into level 1 alarm, level 2 alarm and level 3 alarm according to the urgency of the alarm information and the size of the potential risk. The alarm history record module stores these level information together for subsequent analysis and query. In addition to the above information, the alarm history module also records the processing results and the name and processing time of the person who processed it. This information is crucial for evaluating the effectiveness and efficiency of alarm processing. By querying the processing results, managers can understand whether the alarm has been processed promptly and effectively, and whether there are any problems in the processing process. At the same time, the name and processing time of the person who processed it also provide a basis for responsibility tracing.

[0045] See also Figure 1 In another embodiment, the alarm history recording module also supports visual analysis of alarm data.

[0046] In the above embodiment, after the data preprocessing is completed, the alarm history module starts data analysis. It can select appropriate data dimensions and indicators for analysis according to the needs and interests of the user. For example, the user can view the number of alarms of a specific type in a certain time period, the processing time and the results; or view the density and change trend of alarms in a certain area. After the analysis is completed, the alarm history module will present the analysis results to the user in a visual form. The user can freely adjust the angle and granularity of the data display through the interactive controls on the interface, such as sliders, selectors, zoom buttons, etc. This interactive visual display method enables users to have a deeper understanding of the characteristics of the alarm data.

[0047] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technician familiar with this profession can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A railway intrusion monitoring and alarm system, characterized in that: include: The data acquisition module is used to collect video and radar data along the railway through cameras and millimeter-wave radar equipment to monitor the railway environment in real time; The edge computing module is connected to the data acquisition module to analyze the collected video and radar data in real time, identify potential intruders such as people, animals, and vehicles through intelligent algorithms, and trigger corresponding alarms; A data transmission module, connected to the edge computing module, for transmitting data processed by the edge computing module to the cloud platform; The cloud processing module is connected to the data transmission module, and is used to receive data from the data transmission module, perform secondary judgment and processing, and push the alarm information to the corresponding user; The user interaction module is connected to the cloud processing module to provide a user interface and allow administrators to view alarm information and device status, and support interactive operations between users and the system.

2. The railway perimeter intrusion monitoring and alarm system according to claim 1 is characterized in that: After identifying a potential intruder, if the edge computing module detects that the intruder's movement speed exceeds 5 meters per second, and its movement direction is pointing to the railway track, and the closest distance to the railway track is less than 50 meters, it will be judged as an intrusion through a preset algorithm and an alarm will be triggered.

3. The railway perimeter intrusion monitoring and alarm system according to claim 1 is characterized in that: After receiving the data from the data transmission module, the cloud processing module will verify the timestamp and integrity check code of the data. If the timestamp differs from the current time by more than 5 minutes, or the integrity check code does not match, the data is judged to be incomplete or abnormal, a data error alarm is triggered, and a data retransmission mechanism is started.

4. The railway perimeter intrusion monitoring and alarm system according to claim 1 is characterized in that: The user interaction module allows the administrator to customize the alarm trigger conditions, including but not limited to setting the intruder's moving speed threshold to 3 meters per second, the moving direction range to an angle less than 30 degrees with the railway track, and the safe distance threshold from the railway track to 100 meters. When these conditions are met, an alarm is triggered.

5. The railway perimeter intrusion monitoring and alarm system according to claim 1 is characterized in that: The intelligent learning module automatically adjusts the logical judgment conditions for alarm triggering by analyzing historical data.

6. The railway perimeter intrusion monitoring and alarm system according to claim 5 is characterized in that: The intelligent learning module incorporates the influence of geographic location on intruder behavior, increases the monitoring sensitivity value for animal intrusions in mountainous areas or near wildlife reserves, and reduces the speed threshold for triggering an alarm.

7. The railway perimeter intrusion monitoring and alarm system according to claim 1 is characterized in that: The alarm level management module divides the alarm information into three levels according to the urgency of the alarm information and the size of the potential risk: level one alarm, level two alarm and level three alarm, wherein the triggering condition of the level one alarm includes that the intruder moves at a speed exceeding 5 meters per second and is less than 50 meters from the railway track; the triggering condition of the level two alarm includes that the intruder moves at a speed exceeding 3 meters per second and is less than 100 meters from the railway track; other situations trigger the level three alarm.

8. The railway perimeter intrusion monitoring and alarm system according to claim 7 is characterized in that: The alarm level management module will also include intruder type analysis when classifying alarm levels, and directly trigger a level 1 alarm when a vehicle intrusion is detected.

9. The railway perimeter intrusion monitoring and alarm system according to any one of claims 1 to 8, characterized in that: The alarm history record module will store detailed information of each alarm, including alarm time, longitude and latitude coordinates, intruder type, alarm level, processing result, and name and processing time of the processing personnel.

10. The railway perimeter intrusion monitoring and alarm system according to claim 9, characterized in that: The alarm history recording module also supports visual analysis of alarm data.

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