PCIE slot-based intelligent monitoring device connection method

Abstract

The application discloses a kind of based on PCIE slot's intelligent monitoring device connection method, it is related to intelligent monitoring device configuration technical field, comprising: the connection channel of initialization each functional unit;According to monitoring demand, the required functional unit is selected;The data collected is transmitted to data processing unit by PCIE interface;The data after processing is analyzed, and event is automatically identified according to analysis result;Event is classified based on event identification result;According to demand, hot plug operation is carried out to the functional unit that has been connected in running process.The intelligent monitoring device connection method based on PCIE slot provided in the application effectively improves the resource utilization of intelligent monitoring device, optimizes the response speed of monitoring task, improves the stability and intelligent level of system, solves the unreasonable functional unit configuration, event processing not in time, resource allocation inflexible problem existing in prior art.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring device configuration technology, specifically to a method for connecting an intelligent monitoring device based on a PCIe slot. Background Technology

[0002] Currently, most devices in the field of intelligent monitoring adopt traditional single-function units, resulting in poor system scalability and integration, and an inability to flexibly adapt to different monitoring needs. In addition, the data transmission efficiency of existing technologies is low, and commonly used interfaces such as serial buses and low-speed interfaces have insufficient bandwidth, which cannot meet the requirements of real-time data processing. Especially in multi-channel, multi-data source monitoring scenarios, data lag or loss is likely to occur.

[0003] Furthermore, most existing monitoring systems cannot support hot-swapping during operation, which limits the system's ability to dynamically adjust functional units. If the system needs to be upgraded or its configuration adjusted, manual intervention is usually required by shutting down the equipment, which greatly affects the system's flexibility and stability. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that in the prior art, the selection of functional units, data transmission and processing are not fully optimized for the needs of each monitoring task, resulting in unreasonable equipment resource configuration and inefficient data transmission, which in turn affects the real-time processing capability and stability of the system. In addition, the prior art lacks flexibility in the identification and response to abnormal events, cannot dynamically adjust resources according to real-time changes, and cannot adapt to the processing needs of high-priority events.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for connecting an intelligent monitoring device based on a PCIe slot, comprising:

[0007] Start the device, initialize the connection channels of each functional unit, and detect and confirm the connection status of each functional unit.

[0008] Based on monitoring requirements, select the necessary functional units and configure their operating modes according to the performance parameters of each functional unit.

[0009] The collected data is transmitted to the data processing unit via the PCIe interface for real-time processing.

[0010] The processed data is analyzed, and events are automatically identified based on the analysis results.

[0011] Events are categorized based on event recognition results, and a response mechanism is automatically triggered when preset conditions are met.

[0012] As needed, the system can hot-swap connected functional units during operation, replace or add new functional units, and automatically identify and configure new functional units.

[0013] As a preferred embodiment of the intelligent monitoring device connection method based on PCIE slot described in this invention, the initialization of the connection channels of each functional unit includes automatically detecting the status of all connected functional units through the PCIE bus after starting the device, and determining whether each functional unit is connected normally.

[0014] Assign initial data transmission parameters based on the characteristics of each connected functional unit;

[0015] If any functional unit connection abnormality is detected, the subsequent configuration operation of that unit shall be stopped immediately.

[0016] As a preferred embodiment of the intelligent monitoring device connection method based on PCIe slot described in this invention, the step of selecting the required functional unit includes selecting the functional unit according to the requirements of the current monitoring task;

[0017] The operating mode of each functional unit is determined based on the initial data transmission parameters;

[0018] Adjust the operating mode based on the performance requirements of the selected functional unit;

[0019] Start each selected functional unit and perform initialization operations.

[0020] As a preferred embodiment of the intelligent monitoring device connection method based on PCIe slot described in this invention, the real-time data processing includes, after initiating the data transmission process, segmenting the collected data according to the data type.

[0021] The segmented data packets are transmitted to the data processing unit via the PCIe interface;

[0022] After receiving the data packet, the data processing unit performs real-time processing according to the data type;

[0023] The data after aggregation and processing is based on...

[0024] As a preferred embodiment of the intelligent monitoring device connection method based on PCIe slot described in this invention, the automatic event identification includes, after initiating the data transmission process, segmenting the collected data according to data type; for temperature sensor data, dividing the data into time series according to sampling time; for video data, dividing the data into frames according to frame rate; and for motion sensor data, dividing the data into periodic segments according to sampling frequency.

[0025] The segmented data packets are transmitted to the data processing unit via the PCIe interface. During transmission, each data packet is accompanied by a timestamp and a data type tag.

[0026] After receiving the data packet, the data processing unit performs real-time processing according to the data type. For temperature data, the data processing unit uses a temperature change rate algorithm to perform fluctuation analysis and detect in real time whether the temperature change rate exceeds a preset threshold. For video data, the data processing unit uses a convolutional neural network to extract image features and identify abnormal activities in the video. For motion sensor data, the data processing unit performs frequency domain analysis to extract the amplitude and frequency features of the motion.

[0027] For the processed data, the data processing unit combines a preset threshold model with historical data to perform anomaly detection for each type of data. Anomaly detection for temperature data is based on the set upper and lower temperature limits; if the threshold is exceeded, it is marked as anomaly. Anomaly detection for video data is based on a motion trajectory and background difference algorithm; if unauthorized intrusion behavior is detected, it is identified as anomaly. Anomaly detection for motion data is based on a rapid change algorithm; if the change in motion amplitude exceeds a preset threshold, it is marked as anomaly.

[0028] As a preferred embodiment of the intelligent monitoring device connection method based on PCIe slots described in this invention, the classification includes classifying all identified abnormal events according to priority, dividing them into high priority, medium priority and low priority.

[0029] As a preferred embodiment of the intelligent monitoring device connection method based on PCIe slots described in this invention, the hot-plugging operation includes automatically determining whether a hot-plugging operation is needed based on the priority of various abnormal events.

[0030] After determining that a hot-swap operation is to be performed, select the appropriate functional unit for plugging or unplugging based on the type and priority of the abnormal event and the current load.

[0031] Perform hot-plug operations based on the selected functional unit;

[0032] After the hot-plug operation is completed, the working mode of the functional unit is automatically adjusted based on the current resource load.

[0033] After the hot-swap operation is completed, the status of the new functional unit is monitored in real time to ensure that all functions of the new unit are operating normally.

[0034] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the intelligent monitoring device connection method based on a PCIe slot as described above.

[0035] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the intelligent monitoring device connection method based on a PCIe slot as described above.

[0036] The beneficial effects of this invention are as follows: The intelligent monitoring device connection method based on a PCIe slot provided by this invention improves processing power and flexibility by intelligently configuring and optimizing each functional unit; secondly, in the identification and priority classification of abnormal events, resources are flexibly adjusted according to real-time needs and load conditions, avoiding performance degradation caused by excessive system load; in addition, the introduction of hot-swapping function further enhances the scalability and adaptability of the system, enabling the monitoring device to dynamically replace or add functional units without affecting normal operation, adapting to the needs of different monitoring tasks.

[0037] The implementation of this method effectively improves the resource utilization rate of intelligent monitoring devices, optimizes the response speed of monitoring tasks, enhances the stability and intelligence level of the system, and solves the problems of unreasonable configuration of functional units, untimely event processing, and inflexible resource allocation in existing technologies. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is an overall flowchart of a method for connecting an intelligent monitoring device based on a PCIe slot, as provided in one embodiment of the present invention. Detailed Implementation

[0040] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0041] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0042] Example 1

[0043] Reference Figure 1 As one embodiment of the present invention, a method for connecting an intelligent monitoring device based on a PCIe slot is provided, comprising:

[0044] Start the device, initialize the connection channels of each functional unit, and detect and confirm the connection status of each functional unit.

[0045] Based on monitoring requirements, select the necessary functional units and configure their operating modes according to the performance parameters of each functional unit.

[0046] The collected data is transmitted to the data processing unit via the PCIe interface for real-time processing.

[0047] The processed data is analyzed, and events are automatically identified based on the analysis results.

[0048] Events are categorized based on event recognition results, and a response mechanism is automatically triggered when preset conditions are met.

[0049] As needed, the system can hot-swap connected functional units during operation, replace or add new functional units, and automatically identify and configure new functional units.

[0050] The initialization of the connection channels of each functional unit includes automatically detecting the status of all connected functional units through the PCIE bus after the device is started, and determining whether each functional unit is connected normally.

[0051] Assign initial data transmission parameters based on the characteristics of each connected functional unit;

[0052] If any functional unit connection abnormality is detected, the subsequent configuration operation of that unit shall be stopped immediately.

[0053] Specifically, the process of initializing the connection channels of each functional unit can be automated through the PCIe bus. Upon device startup, the system first sends initialization signals to each connected functional unit, triggering self-testing and status feedback. Each functional unit transmits its connection status to the main control unit via feedback status information (such as whether it is properly connected, power status, etc.). The main control unit determines whether each functional unit is in normal working condition based on this information. Furthermore, after receiving the status information, the main control unit checks parameters such as signal strength, data transmission rate, and connection stability of each functional unit. If an anomaly is detected in a functional unit, such as signal interruption or power fluctuation, the system immediately executes the anomaly handling procedure, automatically stopping the configuration operation of that unit and notifying the operator to resolve the issue as quickly as possible. It should be noted that during this process, the system automatically generates an anomaly log and stores it in the database, ensuring more efficient subsequent troubleshooting and equipment maintenance.

[0054] The selection of the required functional unit includes selecting the functional unit according to the requirements of the current monitoring task;

[0055] The operating mode of each functional unit is determined based on the initial data transmission parameters;

[0056] Adjust the operating mode based on the performance requirements of the selected functional unit;

[0057] Start each selected functional unit and perform initialization operations.

[0058] Specifically, the process of selecting the required functional units first dynamically selects suitable functional units based on the actual needs of the monitoring task. For example, when monitoring temperature, the system will prioritize temperature sensor units for data acquisition according to task requirements. Furthermore, during the selection process, the system configures the operating mode of each functional unit based on its performance parameters (such as sampling accuracy, data processing capability, power consumption, etc.). For high-precision sensors, the system will configure a high-frequency mode to ensure the accuracy of temperature data acquisition; while for scenarios requiring low power consumption, the system will configure a low-power mode for certain sensors to extend the lifespan of the equipment. It should be noted that this configuration process not only relies on the basic characteristics of the equipment but also comprehensively considers the current workload, resource status, and overall system performance requirements. When the performance of a certain functional unit does not meet the current monitoring needs, the system will reselect or adjust the required functional units according to preset rules.

[0059] The real-time data processing includes, after initiating the data transmission process, segmenting the collected data according to data type. For video data, each frame is cut into multiple small data packets, each data packet not exceeding the set maximum transmission unit size. For sensor data, it is divided into data packets with fixed time windows based on sampling time, each packet containing several sensor data points.

[0060] The segmented data packets are transmitted to the data processing unit via the PCIe interface. During data transmission, the bandwidth control mechanism of the PCIe bus is used to regulate the flow, ensuring that the data packets are delivered to the data processing unit in order and without loss.

[0061] After receiving the data packet, the data processing unit performs real-time processing according to the data type. For video data, it performs image denoising, dynamic target detection, and inter-frame difference analysis; for sensor data, it applies algorithms such as data filtering, outlier removal, and smoothing to reduce noise and extract stable trend information.

[0062] The data after aggregation and processing is based on...

[0063] Specifically, the real-time data processing steps involve the segmentation and transmission of different data types. The system first identifies the type of the collected data. For temperature sensor data, the system segments the data according to a time series based on timestamps and sampling frequency; for video data, the system segments it frame by frame based on frame rate; and for motion sensor data, it segments it according to a set periodicity. Further, after each type of data is segmented, it is transmitted to the data processing unit via a PCIe interface. Each data packet carries necessary timestamps and data type tags during transmission to ensure accurate data processing at the receiving end. The data processing unit selects an appropriate real-time processing algorithm based on the data type. For example, for temperature data, a temperature change rate algorithm is used; for video data, a convolutional neural network (CNN) is used for image feature extraction; and for motion data, relevant features are extracted through frequency domain analysis. It should be noted that timestamp and tag information during data transmission is crucial for ensuring data timeliness and consistency, especially during high-frequency or large-scale data transmission, effectively preventing data loss and processing delays.

[0064] The automatic event identification includes, after initiating the data transmission process, segmenting the collected data according to data type; for temperature sensor data, dividing the data into time series according to sampling time; for video data, dividing it into frames according to frame rate; and for motion sensor data, dividing it into periodic segments according to sampling frequency.

[0065] The segmented data packets are transmitted to the data processing unit via the PCIe interface. During transmission, each data packet is accompanied by a timestamp and a data type tag.

[0066] After receiving the data packet, the data processing unit performs real-time processing according to the data type. For temperature data, the data processing unit uses a temperature change rate algorithm to perform fluctuation analysis and detect in real time whether the temperature change rate exceeds a preset threshold. For video data, the data processing unit uses a convolutional neural network to extract image features and identify abnormal activities in the video. For motion sensor data, the data processing unit performs frequency domain analysis to extract the amplitude and frequency features of the motion.

[0067] For the processed data, the data processing unit combines a preset threshold model with historical data to perform anomaly detection for each type of data. Anomaly detection for temperature data is based on the set upper and lower temperature limits; if the threshold is exceeded, it is marked as anomaly. Anomaly detection for video data is based on a motion trajectory and background difference algorithm; if unauthorized intrusion behavior is detected, it is identified as anomaly. Anomaly detection for motion data is based on a rapid change algorithm; if the change in motion amplitude exceeds a preset threshold, it is marked as anomaly.

[0068] Furthermore, the automatic event identification process is performed after data transmission and processing. For different types of data, the system employs different processing algorithms to analyze the data in real time. For example, for temperature data, the system calculates the rate of temperature change in real time and compares it with a preset threshold to determine if it exceeds the set range. For video data, the system uses a convolutional neural network (CNN) for image recognition, extracts motion trajectory features, and analyzes for abnormal behavior, such as unauthorized intrusion. For motion sensor data, the system uses an algorithm based on frequency and amplitude changes to detect abnormal fluctuations in real time. It should be noted that after data processing, the system not only detects local data but also combines historical data and background knowledge for global anomaly identification. For example, the system adjusts the threshold based on historical temperature change patterns to make anomaly detection for temperature data more accurate; while the anomaly identification algorithm for video data is trained based on past intrusion patterns, further improving the accuracy of intrusion detection.

[0069] The classification process includes categorizing all identified abnormal events by priority into high priority, medium priority, and low priority.

[0070] Furthermore, the process of classifying abnormal events goes beyond a preliminary judgment based on the severity of the event; it also comprehensively considers system resources, load conditions, and time urgency. For example, when the system detects a high-priority event (such as abnormal temperature or intrusion), it immediately triggers the corresponding response mechanism, prioritizing resource allocation for processing. It should be noted that the system adjusts priorities based on the specific context of the event (such as sensor location, current load conditions, etc.) to ensure that high-priority events receive timely responses, while low-priority events are processed gradually as the load allows. For medium-priority events, the system rationally allocates resources based on current processing capacity to avoid slow responses or excessive resource consumption. Through this multi-dimensional priority classification, the system can maintain efficient operation in complex environments.

[0071] The hot-swapping operation involves automatically determining whether a hot-swapping operation is needed based on the priority of various abnormal events. For high-priority events, if the currently connected functional units cannot meet the processing requirements, the system immediately initiates a hot-swapping operation to add or replace the relevant functional units. For medium-priority events, if the existing functional units can handle the situation effectively but their processing capacity is nearing its limit, the system will choose to moderately expand the system while maintaining the operation of the current units, based on resource load conditions. For low-priority events, the system typically does not perform hot-swapping operations unless the same type of low-priority event is detected multiple times, in which case the system will decide whether to make adjustments.

[0072] After determining that a hot-swap operation is to be performed, the appropriate functional unit is selected for insertion or removal based on the type and priority of the abnormal event and the current load. For example, for high-priority temperature anomalies, the system prioritizes inserting functional units with temperature control or environmental monitoring capabilities; for medium-priority motion data anomalies, if the existing unit can process the data but is inefficient, the system selects to add a motion analysis unit with stronger computing power for auxiliary processing; for low-priority minor sensor fluctuations, if the detected event is continuous and close to the threshold, the system selects to add a data processing unit with a larger bandwidth to prevent data loss.

[0073] Hot-plugging is performed based on the selected functional unit. During this process, the system adaptively configures the newly inserted functional unit via the PCIe bus, ensuring seamless integration and seamless operation with existing units. All data transmission and control signals remain stable throughout the hot-plugging process, preventing interruptions to data flow or disruption to existing monitoring tasks.

[0074] After a hot-swap operation is completed, the operating mode of the functional unit is automatically adjusted based on the current resource load. If the hot-swap operation is for a high-priority event, the system will prioritize configuring the newly added functional unit in high-efficiency processing mode; for medium-priority events, the system will adjust the operating mode of the newly added unit to balanced mode to avoid excessive consumption of system resources; for low-priority events, the newly added unit will be adjusted to low-power mode to ensure reasonable allocation of system resources.

[0075] After a hot-swap operation is completed, the status of the new functional unit is monitored in real time to ensure that all functions of the new unit operate normally. Status feedback is transmitted to the data processing unit, and further optimization is performed based on the new load distribution. After anomalies are handled, the system reassesses whether further hot-swap operations are needed based on the frequency, type, and priority of new events.

[0076] Specifically, the hot-swap operation first determines whether a hot-swap is necessary based on the type and priority of the abnormal event and the current system load. When the system detects a high-priority event (such as device failure or performance degradation under high load), it immediately initiates the hot-swap process to optimize system resource allocation. Further, after determining to perform the hot-swap operation, the system selects the most suitable functional unit for plugging or swapping based on the specific type of abnormal event. For example, if a temperature sensor fails, the system may select a sensor with higher accuracy or stability for replacement; if a data transmission module fails, the system may select a module with higher bandwidth for plugging or swapping. It should be noted that after the hot-swap operation is completed, the system immediately performs a status check on the new functional unit and reconfigures its operating mode according to the current resource load to ensure perfect collaboration with the existing system. Simultaneously, the system monitors the performance of the new functional unit in real time and continuously optimizes its configuration based on data feedback to ensure the system's high efficiency and stability.

[0077] Example 2

[0078] One embodiment of the present invention differs from the previous embodiment in that:

[0079] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0080] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0081] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0082] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for connecting an intelligent monitoring device based on a PCIe slot, characterized in that, include: Start the device, initialize the connection channels of each functional unit, and detect and confirm the connection status of each functional unit. Based on monitoring requirements, select the necessary functional units and configure their operating modes according to the performance parameters of each functional unit. The collected data is transmitted to the data processing unit via the PCIe interface for real-time processing. The processed data is analyzed, and events are automatically identified based on the analysis results. Events are categorized based on event recognition results, and a response mechanism is automatically triggered when preset conditions are met. As needed, the system can hot-swap connected functional units during operation, replace or add new functional units, and automatically identify and configure new functional units. The hot-plugging operation includes automatically determining whether a hot-plugging operation is needed based on the priority of various abnormal events. For high-priority events, if the currently connected functional units cannot meet the processing requirements, the system immediately initiates a hot-plugging operation to add or replace the relevant functional units. For medium-priority events, if the existing functional units can effectively handle the situation, but their processing capacity is close to its limit, the system will choose to moderately expand the system while maintaining the operation of the current units, based on the resource load. For low-priority events, the system does not perform a hot-plugging operation unless the same type of low-priority event is detected multiple times, in which case the system will decide whether to make adjustments. After determining that a hot-swap operation is to be performed, the appropriate functional unit is selected for plugging or unplugging based on the type and priority of the abnormal event and the current load. Perform hot-plug operations based on the selected functional units, and adaptively configure the newly inserted functional units through the PCIe bus to ensure that they can be seamlessly connected and work together with existing units. During the hot-plug process, all data transmission and control signals remain stable to avoid interrupting the data flow or affecting the normal operation of existing monitoring tasks. After the hot-plug operation is completed, the working mode of the functional unit is automatically adjusted based on the current resource load. The system monitors the status of new functional units in real time and ensures that all functions of the new units operate normally; it transmits status feedback to the data processing unit and further optimizes the system based on the new load distribution; after an abnormal event is handled, the system reassesses whether further hot-plugging operations are needed based on the frequency, type, and priority of the new event.

2. The connection method for an intelligent monitoring device based on a PCIe slot as described in claim 1, characterized in that: The initialization of the connection channels of each functional unit includes automatically detecting the status of all connected functional units through the PCIE bus after the device is started, and determining whether each functional unit is connected normally. Assign initial data transmission parameters based on the characteristics of each connected functional unit; If any functional unit connection abnormality is detected, the subsequent configuration operation of that unit shall be stopped immediately.

3. The connection method for an intelligent monitoring device based on a PCIe slot as described in claim 2, characterized in that: The selection of the required functional unit includes selecting the functional unit according to the requirements of the current monitoring task; The operating mode of each functional unit is determined based on the initial data transmission parameters; Adjust the operating mode based on the performance requirements of the selected functional unit; Start each selected functional unit and perform initialization operations.

4. The connection method for an intelligent monitoring device based on a PCIe slot as described in claim 3, characterized in that: The real-time data processing includes, after initiating the data transmission process, segmenting the collected data according to data type; The segmented data packets are transmitted to the data processing unit via the PCIe interface; After receiving the data packet, the data processing unit performs real-time processing according to the data type; The data after aggregation and processing is based on...

5. The intelligent monitoring device connection method based on a PCIe slot as described in claim 4, characterized in that: The automatic event identification includes, after initiating the data transmission process, segmenting the collected data according to data type; For temperature sensor data, the data is divided into time series according to sampling time; for video data, it is divided into frames according to frame rate; for motion sensor data, it is divided into periodic segments according to sampling frequency. The segmented data packets are transmitted to the data processing unit via the PCIe interface. During transmission, each data packet is accompanied by a timestamp and a data type tag.

6. The connection method for an intelligent monitoring device based on a PCIe slot as described in claim 5, characterized in that: After receiving the data packet, the data processing unit performs real-time processing according to the data type. For temperature data, the data processing unit uses a temperature change rate algorithm to perform fluctuation analysis and detect in real time whether the temperature change rate exceeds a preset threshold. For video data, the data processing unit uses a convolutional neural network to extract image features and identify abnormal activities in the video. For motion sensor data, the data processing unit performs frequency domain analysis to extract the amplitude and frequency features of the motion. After processing, the data processing unit combines the preset threshold model with historical data to perform anomaly detection for each type of data. Anomaly detection for temperature data is based on the set upper and lower temperature limits. If the threshold is exceeded, it is marked as an anomaly. Video data anomaly detection uses an algorithm that compares motion trajectories with the background; if unauthorized intrusion behavior is detected, it is identified as an anomaly. Anomaly detection in motion data is based on a fast change algorithm; if the change in motion amplitude exceeds a preset threshold, it is marked as an anomaly.

7. The connection method for an intelligent monitoring device based on a PCIe slot as described in claim 6, characterized in that: The classification process includes categorizing all identified abnormal events by priority into high priority, medium priority, and low priority.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent monitoring device connection method based on a PCIe slot as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent monitoring device connection method based on a PCIe slot as described in any one of claims 1 to 7.

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