Conference intelligent operation and maintenance management and control method, system and equipment

Abstract

The invention discloses a conference intelligent operation and maintenance management and control method, system and equipment. The method comprises the following steps: S1, performing instruction translation on a private protocol calling protocol adapter; s2, performing dynamic periodic state detection on the equipment according to an elastic scheduling algorithm, and generating a health degree report; s3, using an LSTM prediction model to carry out fault diagnosis on the equipment based on the time sequence data, and triggering an emergency response; s4, realizing multi-device centralized monitoring through video stream transcoding and KVM remote control; according to the invention, based on a dynamic protocol adaptation mechanism, a compatibility barrier caused by independent operation of multiple systems is eliminated, and the operation and maintenance efficiency is improved; a fault point is accurately locked in combination with an LSTM time sequence prediction model and a video stream transcoding technology, and rapid fault positioning and emergency link switching are realized by using a self-adaptive code rate; based on an elastic routing inspection algorithm and a health degree report automatic generation function, the invalid routing inspection frequency of low-risk equipment is remarkably reduced, and the operation and maintenance cost is reduced.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance management technology, specifically to a method, system, and equipment for intelligent operation and maintenance management of conferences. Background Technology

[0002] Equipment operation and maintenance management is used in scenarios such as large conference rooms, lecture halls, and command centers. Its core purpose is to monitor and control various audio-visual equipment, IoT devices, and network devices. However, it still has some shortcomings:

[0003] First, the existing operation and maintenance system relies on independent subsystems to manage audio and video devices, IoT devices and network devices separately, lacking a unified protocol conversion mechanism; device access requires manual configuration of dedicated interfaces and protocol parsers, resulting in poor compatibility and difficulty in expansion, and cross-system operations require frequent switching of management interfaces, leading to low operation and maintenance efficiency;

[0004] Secondly, traditional solutions trigger alarms by setting preset thresholds, but cannot distinguish between occasional fluctuations and real faults, resulting in a high false alarm rate; fault location requires maintenance personnel to check the equipment links on-site, which is time-consuming; remote diagnosis is limited by video transmission lag, making it difficult to obtain effective information in real time.

[0005] Finally, routine inspections use a fixed cycle pattern, which cannot distinguish the risk level of equipment; excessive inspection of low-risk equipment consumes resources, while critical equipment is inspected too infrequently, resulting in delayed fault warnings and high maintenance costs.

[0006] Therefore, it is necessary to design a method, system, and equipment for intelligent operation and maintenance management of meetings. Summary of the Invention

[0007] The purpose of this invention is to provide a method, system, and device for intelligent operation and maintenance management of conferences, in order to solve the problems mentioned in the background art. These problems include: existing operation and maintenance systems rely on independent subsystems to manage audio / video devices, IoT devices, and network devices separately, lacking a unified protocol conversion mechanism; device access requires manual configuration of dedicated interfaces and protocol parsers, resulting in poor compatibility and difficulty in expansion; cross-system operations require frequent switching of management interfaces, leading to low operation and maintenance efficiency; traditional solutions trigger alarms through preset thresholds, but cannot distinguish between occasional fluctuations and real faults, resulting in a high false alarm rate; fault location requires on-site inspection of equipment links by operation and maintenance personnel, which is time-consuming; remote diagnosis is limited by video transmission lag, making it difficult to obtain effective information in real time; routine inspections use a fixed-cycle mode, which cannot distinguish the risk level of equipment; excessive testing of low-risk equipment consumes resources, while the testing frequency of critical equipment is insufficient, leading to delayed fault warnings and high operation and maintenance costs.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] Firstly, a method for intelligent operation and maintenance management of meetings is provided, including the following steps:

[0010] S1: Collect operational data from heterogeneous devices through a multi-protocol interface module, identify device protocol types through a dynamic parsing engine, and translate instructions for private protocols by calling the protocol adapter; the heterogeneous devices include audio and video devices, IoT devices, and network devices.

[0011] S2: Define the device criticality weight w according to the elastic scheduling algorithm. i It performs dynamic and periodic status checks on the equipment and generates health reports;

[0012] S3: Use an LSTM prediction model to diagnose equipment faults based on time-series data and trigger an emergency response;

[0013] S4: Enables centralized monitoring of multiple devices through video stream transcoding and KVM remote control.

[0014] As a further technical solution of the present invention, the protocol adapter is invoked in S1 to perform instruction translation, and the translation formula is as follows:

[0015] C std =Φ(P raw ,Θ)

[0016] Among them, C std For standard instructions; P raw Θ represents the original instruction; Θ represents the protocol mapping parameter set.

[0017] The protocol mapping parameter set Θ is generated by the protocol adapter through the following steps:

[0018] Extract the instruction feature vector F = {f1, f2, ..., f n}, f i Including instruction length and checksum mode;

[0019] Cosine similarity matching protocol library:

[0020]

[0021] Choose sin max The protocol template with a value >0.8 generates the protocol mapping parameter set Θ.

[0022] As a further technical solution of the present invention, the elastic scheduling algorithm in S2 includes:

[0023] Define the criticality weight of the device: w i = α·failure frequency + β·business impact;

[0024] Dynamically adjust inspection intervals:

[0025] T i =T base / log(1+w i )

[0026] Among them, T base This is the basic inspection cycle.

[0027] As a further technical solution of the present invention, the health report generation step in S2 is as follows:

[0028] Calculate the device health index:

[0029]

[0030] If H < 0.7, it is automatically marked as a high-risk device.

[0031] As a further technical solution of the present invention, the LSTM prediction model in S3 includes:

[0032] Input layer: Receive device timing data X t ={x1,x2,...,x t}, x i Includes temperature, network packet loss rate, and signal strength;

[0033] Hidden layer: The state is updated through a gating mechanism; the forget gate is calculated as follows:

[0034] f t =σ(W f ·[h t-1 ,x t ]+b f )

[0035] Among them, w f b is the weight matrix; f σ is the bias term; σ is the sigmoid function.

[0036] Output layer: Generates the failure probability y t =s(W y ·h t +b y If y t If the threshold is greater than δ, it is considered a fault.

[0037] LSTM prediction model training includes:

[0038] The loss function uses weighted cross-entropy;

[0039]

[0040] Where, γ t y is the time-series decay factor; t This is a real label.

[0041] As a further technical solution of the present invention, the emergency response in S3 includes:

[0042] If the fault is in a network device, automatically switch to the backup link;

[0043] Alarm information is pushed to the operation and maintenance terminal via the 4G module. The alarm information includes the faulty device ID, location path and handling suggestions.

[0044] As a further technical solution of the present invention, the video stream transcoding in S4 includes:

[0045] Input the raw video stream via the HDMI interface;

[0046] Transcoded to RTSP stream using an H.264 encoder, with an adaptive bitrate formula:

[0047]

[0048] Among them, R in R is the raw input bitrate, referring to the data rate of the raw video stream captured via the HDMI interface. out The output bitrate is the data rate of the RTSP video stream after transcoding by the H.264 encoder; k is a constant for the encoding compression coefficient.

[0049] As a further technical solution of the present invention, the KVM remote control in S4 includes:

[0050] Connect the controlled device via USB-B interface;

[0051] Local operation commands are mapped to device command sets, and the mapping table is stored on the SD card.

[0052] Secondly, a meeting intelligent operation and maintenance management system is provided, including:

[0053] Protocol fusion module: integrates multi-protocol interfaces RJ45 / RS-485 / DMX512, and protocol adapters to realize command translation;

[0054] Intelligent diagnostic module: Runs an LSTM prediction model and outputs the probability and location of the fault;

[0055] Flexible inspection module: Dynamically adjusts the inspection frequency according to the criticality of the equipment;

[0056] Video processing module: Supports HDMI to RTSP streaming and cross-network transmission;

[0057] Emergency control module: performs link switching and alarm push.

[0058] Thirdly, a smart conference operation and maintenance management device is provided, including:

[0059] Hardware layer:

[0060] Multi-protocol interface module: integrates ≥8 RJ45 ports supporting PoE and ≥4 RS-485 ports;

[0061] Video processing chip: Enables simultaneous encoding and decoding, as well as RTSP transcoding;

[0062] 4G module and SD card slot;

[0063] Software layer:

[0064] The embedded system runs any of the methods in the first aspect.

[0065] Compared with existing technologies, the beneficial effects of this intelligent conference operation and maintenance management method, system, and equipment are:

[0066] Based on the dynamic protocol adaptation mechanism, the system automatically translates instructions for private audio and video protocols, IoT and network device protocols by extracting instruction features and matching protocol templates. This eliminates compatibility barriers caused by independent operation of multiple systems, enabling heterogeneous devices to be centrally controlled on a unified platform and improving operation and maintenance efficiency.

[0067] By combining LSTM timing prediction models with video stream transcoding technology, the fault point can be accurately located by analyzing the timing correlation of equipment operating parameters, and adaptive bitrate adjustment can be used to ensure the smoothness of remote video diagnosis, thereby achieving rapid fault location and emergency link switching.

[0068] By leveraging the flexible inspection algorithm to dynamically allocate inspection resources and automatically adjust the inspection frequency based on the criticality of equipment, combined with the automatic generation function of health reports, the frequency of ineffective inspections of low-risk equipment is significantly reduced, forming a closed-loop optimization of resource allocation and risk management, thereby reducing operation and maintenance costs. Attached Figure Description

[0069] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0070] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0071] Please see the appendix Figure 1 The present invention provides an embodiment of a meeting intelligent operation and maintenance management method, comprising the following steps:

[0072] S1: Collect operational data from heterogeneous devices through a multi-protocol interface module, identify device protocol types through a dynamic parsing engine, and translate instructions for private protocols by calling the protocol adapter; the heterogeneous devices include audio and video devices, IoT devices, and network devices.

[0073] The protocol adapter is invoked for instruction translation, and the translation formula is as follows:

[0074] C std =Φ(P raw ,Θ)

[0075] Among them, C std For standard instructions; P raw Θ represents the original instruction; Θ represents the protocol mapping parameter set.

[0076] The protocol mapping parameter set Θ is generated by the protocol adapter through the following steps:

[0077] Extract the instruction feature vector F = {f1, f2, ..., f n}, f i Including instruction length and checksum mode;

[0078] Cosine similarity matching protocol library:

[0079]

[0080] Choose sin max A protocol template with a value >0.8 generates a protocol mapping parameter set Θ;

[0081] S2: Define the device criticality weight w according to the elastic scheduling algorithm. i The system performs dynamic, periodic status checks on the equipment and generates health reports.

[0082] Define device criticality weights: w i = α·failure frequency + β·business impact;

[0083] Dynamically adjust inspection intervals:

[0084] T i =T base / log(1+w i )

[0085] Among them, T base Basic inspection cycle;

[0086] Steps to generate a health report:

[0087] Calculate the device health index:

[0088]

[0089] If H < 0.7, it is automatically marked as a high-risk device;

[0090] S3: Use an LSTM prediction model to diagnose equipment faults based on time-series data and trigger an emergency response;

[0091] LSTM prediction models include:

[0092] Input layer: Receive device timing data X t ={x1,x2,...,x t}, x i Includes temperature, network packet loss rate, and signal strength;

[0093] Hidden layer: The state is updated through a gating mechanism; the forget gate is calculated as follows:

[0094] f t =σ(W f ·[h t-1 ,x t ]+b f )

[0095] Among them, W f b is the weight matrix; f σ is the bias term; σ is the sigmoid function.

[0096] Output layer: Generates the failure probability y t =s(W y ·h t +b y If y t If the threshold is greater than δ, it is considered a fault.

[0097] LSTM prediction model training includes:

[0098] The loss function uses weighted cross-entropy;

[0099]

[0100] Where, γ t y is the time-series decay factor; t This is a real label;

[0101] Emergency response includes:

[0102] If the fault is in a network device, automatically switch to the backup link;

[0103] Alarm information is pushed to the operation and maintenance terminal via the 4G module. The alarm information includes the faulty device ID, location path and handling suggestions.

[0104] S4: Enables centralized monitoring of multiple devices via video stream transcoding and KVM remote control;

[0105] Video stream transcoding includes:

[0106] Input the raw video stream via HDMI interface;

[0107] Transcoded to RTSP stream using an H.264 encoder, with an adaptive bitrate formula:

[0108]

[0109] Among them, R in R is the raw input bitrate, referring to the data rate of the raw video stream captured via the HDMI interface. out The output bitrate is the data rate of the RTSP video stream after transcoding by the H.264 encoder; k is a constant for the encoding compression coefficient.

[0110] KVM remote control includes:

[0111] Connect the controlled device via USB-B interface;

[0112] Local operation commands are mapped to device command sets, and the mapping table is stored on the SD card.

[0113] One embodiment of the present invention provides: a conference intelligent operation and maintenance management system, comprising:

[0114] Protocol fusion module: integrates multi-protocol interfaces RJ45 / RS-485 / DMX512, and protocol adapters to realize command translation;

[0115] Intelligent diagnostic module: Runs an LSTM prediction model and outputs the probability and location of the fault;

[0116] Flexible inspection module: Dynamically adjusts the inspection frequency according to the criticality of the equipment;

[0117] Video processing module: Supports HDMI to RTSP streaming and cross-network transmission;

[0118] Emergency control module: performs link switching and alarm push.

[0119] One embodiment of the present invention provides: a conference intelligent operation and maintenance management device, comprising:

[0120] Hardware layer:

[0121] Multi-protocol interface module: integrates ≥8 RJ45 ports supporting PoE and ≥4 RS-485 ports;

[0122] Video processing chip: Enables simultaneous encoding and decoding, as well as RTSP transcoding;

[0123] 4G module and SD card slot;

[0124] Software layer:

[0125] An embedded system that runs a meeting intelligent operation and maintenance management method.

[0126] In summary, this invention, based on a dynamic protocol adaptation mechanism, automatically translates instructions for proprietary audio and video protocols, IoT and network device protocols through instruction feature extraction and protocol template matching. This eliminates compatibility barriers caused by independent operation of multiple systems, enabling heterogeneous devices to be centrally controlled on a unified platform and improving operational efficiency.

[0127] By combining LSTM timing prediction models with video stream transcoding technology, the fault point can be accurately located by analyzing the timing correlation of equipment operating parameters, and adaptive bitrate adjustment can be used to ensure the smoothness of remote video diagnosis, thereby achieving rapid fault location and emergency link switching.

[0128] By leveraging the flexible inspection algorithm to dynamically allocate inspection resources and automatically adjust the inspection frequency based on the criticality of equipment, combined with the automatic generation function of health reports, the frequency of ineffective inspections of low-risk equipment is significantly reduced, forming a closed-loop optimization of resource allocation and risk management, thereby reducing operation and maintenance costs.

[0129] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for intelligent operation and maintenance management of meetings, characterized in that: Includes the following steps: S1: Collect operational data from heterogeneous devices through a multi-protocol interface module, identify device protocol types through a dynamic parsing engine, and translate instructions for private protocols by calling the protocol adapter; the heterogeneous devices include audio and video devices, IoT devices, and network devices. S2: Define the device criticality weight w according to the elastic scheduling algorithm. i It performs dynamic and periodic status checks on the equipment and generates health reports; S3: Use an LSTM prediction model to diagnose equipment faults based on time-series data and trigger an emergency response; S4: Enables centralized monitoring of multiple devices through video stream transcoding and KVM remote control.

2. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: In S1, the protocol adapter is invoked for instruction translation, and the translation formula is as follows: C std =Φ(P raw ,I) Among them, C std For standard instructions; P raw Θ represents the original instruction; Θ represents the protocol mapping parameter set. The protocol mapping parameter set Θ is generated by the protocol adapter through the following steps: Extract the instruction feature vector F = {f1, f2, ..., f n }, f i Including instruction length and checksum mode; Cosine similarity matching protocol library: Choose sin max The protocol template with a value >0.8 generates the protocol mapping parameter set Θ.

3. The intelligent operation and maintenance management method for meetings according to claim 2, characterized in that: The elastic scheduling algorithm in S2 includes: Define the criticality weight of the device: w i = α·failure frequency + β·business impact; Dynamically adjust inspection intervals: T i =T base / log(1+w i ) Among them, T base This is the basic inspection cycle.

4. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: The health report generation steps in S2 are as follows: Calculate the device health index: If H < 0.7, it is automatically marked as a high-risk device.

5. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: The LSTM prediction model in S3 includes: Input layer: Receive device timing data X t ={x1,x2,...,x t }, x i Includes temperature, network packet loss rate, and signal strength; Hidden layer: The state is updated through a gating mechanism; the forget gate is calculated as follows: f t =σ(W f ·[h t-1 ,x t ]+b f ) Among them, W f b is the weight matrix; f σ is the bias term; σ is the sigmoid function. Output layer: Generates the failure probability y t =s(W y ·h t +b y If y t If the threshold is greater than δ, it is considered a fault. LSTM prediction model training includes: The loss function uses weighted cross-entropy; Where, γ t y is the time-series decay factor; t This is a real label.

6. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: The emergency response in S3 includes: If the fault is in a network device, automatically switch to the backup link; Alarm information is pushed to the operation and maintenance terminal via the 4G module. The alarm information includes the faulty device ID, location path and handling suggestions.

7. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: The video stream transcoding in S4 includes: Input the raw video stream via HDMI interface; Transcoded to RTSP stream using an H.264 encoder, with an adaptive bitrate formula: Among them, R in R is the raw input bitrate, referring to the data rate of the raw video stream captured via the HDMI interface. out The output bitrate is the data rate of the RTSP video stream after transcoding by the H.264 encoder; k is a constant for the encoding compression coefficient.

8. The intelligent operation and maintenance management method for meetings according to claim 1, characterized in that: The KVM remote control in S4 includes: Connect the controlled device via USB-B interface; Local operation commands are mapped to device command sets, and the mapping table is stored on the SD card.

9. A conference intelligent operation and maintenance management system, characterized in that: include: Protocol fusion module: integrates multi-protocol interfaces RJ45 / RS-485 / DMX512, and protocol adapters to realize command translation; Intelligent diagnostic module: Runs an LSTM prediction model and outputs the probability and location of the fault; Flexible inspection module: Dynamically adjusts the inspection frequency according to the criticality of the equipment; Video processing module: Supports HDMI to RTSP streaming and cross-network transmission; Emergency control module: performs link switching and alarm push.

10. A conference intelligent operation and maintenance management device, characterized in that: include: Hardware layer: Multi-protocol interface module: integrates ≥8 RJ45 ports supporting PoE and ≥4 RS-485 ports; Video processing chip: Enables simultaneous encoding and decoding, as well as RTSP transcoding; 4G module and SD card slot; Software layer: An embedded system that performs any one of the methods of claims 1-8.

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