Multimedia equipment cluster centralized control method and system for multi-scene scheduling

Abstract

The invention discloses a multimedia equipment cluster centralized control method and system for multi-scene scheduling, and relates to the related field of intelligent regulation and control of multimedia equipment, and the method comprises the steps: carrying out the automatic detection of scenes of a multimedia equipment cluster, obtaining scene state data, and uploading the scene state data to a central control platform; scene identification is carried out to determine a target scene type, scene mapping is carried out, and a multimedia equipment operation parameter rule is obtained; carrying out centralized control on the multimedia equipment group and setting a first centralized control instruction; constructing an equipment topological graph, and performing control verification on the first centralized control instruction to obtain control state information; and traversing the first centralized control instruction according to the control state information to perform dynamic optimization, and constructing a second centralized control instruction to perform centralized cooperative control. The technical problem that it is difficult to efficiently and accurately carry out device cooperative control according to scene dynamic changes in existing multimedia device cluster centralized control is solved, and the technical effect of efficiently and accurately carrying out device cooperative control according to the scene dynamic changes is achieved.

Description

Technical Field

[0001] This application relates to the field of intelligent control of multimedia devices, and in particular to a centralized control method and system for multimedia device clusters for multi-scenario scheduling. Background Technology

[0002] With the increasing prevalence of multimedia devices and the growing diversity of application scenarios, achieving efficient and precise centralized control of multimedia device clusters across multiple scenarios is crucial for improving user experience, ensuring the smooth operation of various activities, and optimizing the utilization of device resources. Currently, the main approach to solving the control problem of multimedia device clusters in multiple scenarios is to design independent control schemes for different scenarios. Each scheme contains a specific set of device control instructions, which are then invoked to control the devices based on preset scenarios, either manually or through simple automated scripts. However, this existing approach lacks a unified scenario awareness and intelligent decision-making mechanism. This results in significant manual intervention required for adjusting device control instructions when switching between different scenarios, leading to low efficiency and a high risk of errors. Furthermore, the lack of coordination between the independent control schemes makes it difficult to optimize device operating parameters in real time according to dynamic changes in the scenario, failing to meet the complex and ever-changing needs of actual scenarios.

[0003] At present, the centralized control of multimedia device clusters faces the technical challenge of efficiently and accurately coordinating device control based on dynamic changes in the scene. Summary of the Invention

[0004] This application provides a centralized control method and system for multimedia device clusters oriented towards multi-scenario scheduling. It employs techniques such as automatically detecting multimedia device cluster scenarios, acquiring scenario status data, uploading it to a central control platform, identifying the scenario and determining the target type, obtaining device operating parameter rules through scenario mapping, setting a first centralized control command based on the rules and target scenario type, constructing a device topology map by connecting the device cluster to the central control platform, verifying the first centralized control command to obtain control status information, dynamically optimizing the first centralized control command based on the control status information, and constructing a second centralized control command for centralized collaborative control. These techniques solve the technical problem of existing centralized control methods for multimedia device clusters being unable to efficiently and accurately perform collaborative device control based on dynamic scenario changes, achieving the technical effect of efficient and accurate collaborative device control based on dynamic scenario changes.

[0005] This application provides a centralized control method for multimedia device clusters oriented towards multi-scenario scheduling, comprising: automatically detecting the scenarios of the multimedia device cluster and uploading the obtained scenario status data to a central control platform; identifying the scenario through the central control platform, determining the target scenario type, mapping the scenario according to the target scenario type, and obtaining multimedia device operating parameter rules; centrally controlling the multimedia device cluster according to the multimedia device operating parameter rules and the target scenario type, and setting a first centralized control command; establishing a communication connection between the multimedia device cluster and the central control platform, constructing a device topology map, verifying the first centralized control command based on the device topology map, and obtaining control status information of the multimedia device cluster; dynamically optimizing the first centralized control command by traversing the control status information of the multimedia device cluster, and constructing a second centralized control command for centralized collaborative control of the multimedia device cluster.

[0006] In a possible implementation, scene recognition is performed through the central control platform to determine the target scene type. Scene mapping is then performed according to the target scene type to obtain multimedia device operating parameter rules. The following processes are then executed: Time-frequency domain feature analysis is performed on the scene state data through the central control platform to construct a scene feature vector; based on the scene feature vector, feature transformation is performed using a multi-layer neural network, and the transformation result is mapped to the scene of the multimedia device group for distribution calculation to obtain scene type probability distribution parameters; hybrid classification is performed according to the scene type probability distribution parameters to generate a scene type recognition result, which includes the target scene type; a scene-device association database is constructed, and the target scene type is used as an index to map to the scene-device association database for retrieval and querying to extract basic device parameter configuration information; the basic device parameter configuration information is dynamically adjusted based on the scene feature vector to construct the multimedia device operating parameter rules.

[0007] In a possible implementation, the basic equipment parameter configuration information is dynamically adjusted based on the scene feature vector to construct the multimedia equipment operating parameter rules, and the following processes are performed: The basic equipment parameter configuration information is parsed to determine the adjustable range of parameters for equipment control analysis, and control constraints are set; the data mapping relationship between the scene feature vector and the basic equipment parameter configuration information is extracted according to the scene-equipment association database; the basic equipment parameter configuration information is adjusted and balanced according to the data mapping relationship to generate an adjustable parameter set, which includes parameter adjustment amount and parameter adjustment direction; multi-objective optimization is performed according to the control constraints, combined with the parameter adjustment amount and parameter adjustment direction, to construct a device parameter adjustment scheme; the device parameter adjustment scheme is executed for simulation verification, and the parameter adjustment effect is obtained to correct the device parameter adjustment scheme, thus constructing the multimedia equipment operating parameter rules.

[0008] In a possible implementation, the device parameter adjustment scheme is executed for simulation verification. The effect of the parameter adjustment is obtained, and the device parameter adjustment scheme is corrected. The operating parameter rules for the multimedia device are constructed, and the following processes are performed: Digital twin simulation is performed based on the target scene type to construct simulation scene parameters; the device parameter adjustment scheme is mapped to the simulation scene parameters for digital twin simulation monitoring to obtain device simulation results, which include device simulation response data and device performance indicators; the device simulation response data is compared and analyzed with the expected operating target value according to the device performance indicators to calculate the parameter adjustment effect, which includes adjustment deviation values ​​for multiple optimization targets; the device parameter adjustment scheme is iteratively corrected based on the adjustment deviation values ​​for the multiple optimization targets to construct the operating parameter rules for the multimedia device.

[0009] In a possible implementation, the multimedia device group is centrally controlled according to the multimedia device operating parameter rules and the target scene type. A first centralized control instruction is set, and the following processes are performed: device identification is performed on the multimedia device group according to the multimedia device operating parameter rules to determine multiple device control targets; device collaboration analysis is performed on the multimedia device group to set device collaboration constraints; multi-scene scheduling impact analysis is performed according to the target scene type to generate a scene scheduling impact sequence; control analysis is performed on the multimedia device group according to the scene scheduling impact sequence to determine device control priorities; and centralized control is performed on the multimedia device group according to the device collaboration constraints, the device control priorities, and the multiple device control targets to generate the first centralized control instruction.

[0010] In a possible implementation, a communication connection is established between the multimedia device group and the central control platform, a device topology graph is constructed, and the following processes are performed: the multimedia device group is traversed and identifiers are assigned, multiple device identifiers are set, the central control platform automatically searches the multimedia device group according to the multiple device identifiers, and an identifier-device mapping relationship is constructed; bidirectional authentication is performed between the multimedia device group and the central control platform according to the identifier-device mapping relationship, and a secure communication connection relationship is constructed; network probing is performed on the multimedia device group based on the secure communication connection relationship, and a network topology relationship is constructed; the physical locations of the multimedia device group are retrieved to perform device dependency analysis and determine device functional dependencies; the physical locations of the multimedia device group are used as nodes, the network topology relationship is used as the connection edges of the nodes, and the device functional dependencies are used as edge weights to construct the device topology graph.

[0011] In a possible implementation, the first centralized control command is verified based on the device topology diagram to obtain control status information of the multimedia device group, and the following processing is performed: control analysis is performed on the multimedia device group based on the first centralized control command to determine device control propagation requirement parameters; centralized control calculation is performed by traversing the device topology diagram according to the physical location of the multimedia device group and the device control propagation requirement parameters to determine the command propagation path; control conflict detection is performed based on the command propagation path, and the command propagation path is updated in reverse according to the control conflict data to generate an optimized command propagation path; the first centralized control command is executed according to the optimized command propagation path to verify control and obtain control status information of the multimedia device group.

[0012] In a possible implementation, the first centralized control instruction is executed according to the optimized instruction propagation path for control verification to obtain the control status information of the multimedia device group. The following processes are then performed: matching the first centralized control instruction with the multimedia device group based on the optimized instruction propagation path to determine the device transmission sequence; performing instruction propagation analysis on the first centralized control instruction according to the device transmission sequence to set the instruction distribution timing; distributing the first centralized control instruction to the multimedia device group according to the instruction distribution timing for real-time monitoring to obtain real-time transmission status information; performing multi-dimensional analysis on the multimedia device group based on the real-time transmission status information to generate multi-dimensional instruction execution effects; performing control verification on the first centralized control instruction based on the multi-dimensional instruction execution effects to construct a device health profile; and adding the device health profile to the control status information of the multimedia device group.

[0013] In a possible implementation, the control status information of the multimedia device group is used to traverse the first centralized control instructions for dynamic optimization, and a second centralized control instruction is constructed to perform centralized collaborative control of the multimedia device group. The following processes are performed: The first centralized control instructions are traversed based on the control status information of the multimedia device group for execution classification to obtain multiple device control status classes; the multiple device control status classes are stored and recorded according to the execution time sequence to construct a status information database; the status information database is traversed and compared with the expected execution status information to identify abnormal device parameters; based on the target scene type and the control status information of the multimedia device group, scene change analysis is performed on the multimedia device group to obtain a scene change dataset; according to the scene change dataset, the abnormal device parameters are mapped to the first centralized control instructions to extract invalid control instructions; device response is adjusted according to the invalid control instructions; and instruction response is optimized by traversing the first centralized control instructions based on the device adjustment parameters to construct the second centralized control instruction.

[0014] This application also provides a centralized control system for multimedia device clusters oriented towards multi-scenario scheduling, comprising: a scene detection module for automatically detecting scenes of the multimedia device cluster and uploading scene status data to a central control platform; a scene mapping module for identifying scenes through the central control platform, determining target scene types, mapping scenes according to the target scene types, and obtaining multimedia device operating parameter rules; a first centralized control instruction setting module for centrally controlling the multimedia device cluster according to the multimedia device operating parameter rules and the target scene types, and setting a first centralized control instruction; a control verification module for establishing a communication connection between the multimedia device cluster and the central control platform, constructing a device topology map, verifying the first centralized control instruction based on the device topology map, and obtaining control status information of the multimedia device cluster; and an instruction optimization module for dynamically optimizing the first centralized control instruction based on the control status information of the multimedia device cluster, constructing a second centralized control instruction for centralized collaborative control of the multimedia device cluster.

[0015] The proposed method and system for centralized control of multimedia device clusters for multi-scenario scheduling first automatically detects the scenarios of the multimedia device cluster, obtains scenario status data, and uploads it to a central control platform. Next, the central control platform identifies the target scenario type, performs scenario mapping according to the target scenario type, obtains multimedia device operating parameter rules, and then centrally controls the multimedia device cluster according to the multimedia device operating parameter rules and the target scenario type, setting a first centralized control command. A communication connection is then established between the multimedia device cluster and the central control platform to construct a device topology map. Based on the device topology map, the first centralized control command is verified to obtain the control status information of the multimedia device cluster. Finally, based on the control status information of the multimedia device cluster, the first centralized control command is dynamically optimized to construct a second centralized control command for centralized collaborative control of the multimedia device cluster. This achieves the technical effect of efficient and accurate collaborative control of devices based on dynamic changes in scenarios. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating a centralized control method for multimedia device clusters oriented towards multi-scenario scheduling, provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the structure of a centralized control system for multi-scenario scheduling of multimedia device clusters provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached diagram: Scene detection module 10, Scene mapping module 20, First centralized control instruction setting module 30, Control verification module 40, Instruction optimization module 50. Detailed Implementation

[0020] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below.

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In the following description, references to "some embodiments" describe a subset of all possible embodiments. However, it is understood that "some embodiments" can be the same or different subsets of all possible embodiments and can be combined with each other without conflict. The terms "first" and "second" are used merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.

[0023] This application provides a centralized control method for multimedia device clusters oriented towards multi-scenario scheduling, such as... Figure 1 As shown, the method includes: Step S100: Automatically detect the scene of the multimedia device group and upload the scene status data to the central control platform.

[0024] Specifically, a sensor network is used to automatically detect the scene of the multimedia device cluster. This sensor network, deployed in the environment where the multimedia device cluster is located, includes, but is not limited to, light sensors, sound sensors, temperature sensors, and motion sensors, used to collect various physical parameters of the environment. The raw data collected by the sensors is preprocessed and analyzed to extract scene-related feature information, generating scene state data which is then uploaded to the central control platform. The scene state data is a collection of parameters describing the current state of the environment in which the multimedia device cluster is located, including light intensity, sound decibels, temperature values, and personnel activity.

[0025] For example, in a conference room scenario, a light sensor is installed on the ceiling to collect real-time data on indoor light intensity; sound sensors are distributed around the perimeter of the conference room to collect ambient sound levels; and motion sensors are installed near the door and conference table to detect people entering, exiting, and moving around. If low light intensity, high sound levels, and frequent movement of people are detected, the scenario is determined to be a meeting in progress, and this scenario characteristic information is integrated into scenario status data and uploaded to the central control platform.

[0026] Step S200: The central control platform is used to identify the scene, determine the target scene type, perform scene mapping according to the target scene type, and obtain the operating parameter rules of the multimedia device.

[0027] Specifically, the central control platform uses a pre-trained scene recognition model to identify the uploaded scene state data and determine the target scene type. This scene recognition model can be based on deep learning convolutional neural networks, recurrent neural networks, or their variants. Trained with a large amount of labeled data, it can classify and identify new, unknown scene data. The specific scene category of the multimedia device group it outputs is the target scene type, such as a meeting scene, a teaching scene, or an entertainment scene.

[0028] After determining the target scene type, the central control platform maps the target scene type to the corresponding multimedia device operating parameter rules according to preset scene mapping rules. Scene mapping is the process of establishing a correspondence between the target scene type and the multimedia device operating parameter rules, ensuring that different scene types correspond to appropriate device operating parameters. The multimedia device operating parameter rules specify the operating parameters that multimedia devices, such as projectors, speakers, and lights, should be set in different scenes. Examples include the brightness and contrast of projectors, the volume and sound effect mode of speakers, and the color and brightness of lights.

[0029] In one possible implementation, scene recognition is performed through the central control platform to determine the target scene type. Scene mapping is then performed according to the target scene type to obtain multimedia device operating parameter rules. Step S200 further includes step S210, where the central control platform performs time-frequency domain feature analysis on the scene state data to construct a scene feature vector. Specifically, the central control platform uses signal processing technology to perform time-frequency domain feature analysis on the scene state data. For example, for time-series signals such as sound signals collected by a sound sensor, Fourier transform is first used to convert them from the time domain to the frequency domain. The energy distribution of the signal at different frequency components is analyzed to obtain frequency domain features, such as the dominant frequency and frequency band energy. At the same time, features such as the signal mean, variance, and peak value are directly extracted from the time domain signal. For non-time-series data such as light intensity data collected by a light sensor, which varies over time, they are processed as a time series, and time-domain and frequency-domain features are extracted in the same way. Then, the extracted features are combined according to certain rules to construct a scene feature vector.

[0030] Step S220: Based on the scene feature vector, feature transformation is performed using a multi-layer neural network. The feature transformation result is then mapped to the scene of the multimedia device group for distribution calculation to obtain scene type probability distribution parameters. Specifically, a pre-trained multi-layer neural network is used to transform the scene feature vector. This multi-layer neural network includes an input layer, multiple hidden layers, and an output layer. The input layer receives the scene feature vector, and the hidden layers perform non-linear transformations on the input features using non-linear activation functions to extract higher-level abstract features. After processing by the multiple hidden layers, the feature transformation result is mapped to the scene space of the multimedia device group. Distribution calculation is performed in the scene space, and the scene type probability distribution parameters are obtained through the output layer of the neural network. These parameters represent the probability that the input scene feature vector belongs to different scene types.

[0031] Step S230: Perform hybrid classification according to the scene type probability distribution parameters to generate a scene type identification result, which includes the target scene type. Specifically, perform hybrid classification based on the scene type probability distribution parameters obtained in step S220, adopting the maximum probability principle, that is, selecting the scene type with the highest probability value among the probability distribution parameters as the preliminary identification result. Simultaneously, to enhance the accuracy and robustness of the classification, a probability threshold can be set. When the maximum probability value exceeds this threshold, it is directly determined as the target scene type; when the maximum probability value does not exceed the threshold, a comprehensive judgment is made in conjunction with other auxiliary information, such as historical scene data and user preset preferences, to finally generate a scene type identification result that includes the target scene type.

[0032] Step S240: Construct a scene-device association database. The target scene type is used as an index to map to the scene-device association database for retrieval and querying, extracting basic device parameter configuration information. Specifically, the scene-device association database is constructed through expert experience or through learning and analysis of a large amount of historical / experimental data. This database is stored in the form of a relational or non-relational database and contains multiple tables, each recording the correspondence between different scene types and the basic parameter configuration information of multimedia devices. The target scene type generated in step S230 is used as an index for retrieval and querying in the scene-device association database. Records matching the target scene type are found in the corresponding tables using database query statements, such as SQL statements, to extract the basic device parameter configuration information.

[0033] Step S250: Based on the scene feature vector, the basic equipment parameter configuration information is dynamically adjusted to construct the multimedia device operating parameter rules. Specifically, based on the scene feature vector constructed in step S210, the special factors and dynamic changes of the current scene are analyzed. For example, if the scene feature vector shows that the light intensity in the current meeting room is stronger than in a normal meeting scene, or the noise level is high, the basic equipment parameter configuration information extracted in step S240 is dynamically adjusted according to these analysis results. The adjustment rules can be preset in the system or obtained through adaptive learning based on historical data using machine learning algorithms. After adjustment, multimedia device operating parameter rules more suitable for the current actual scene are constructed. For example, in a "formal meeting scene," if the scene feature vector shows that the light in the current meeting room is strong, the central control platform dynamically adjusts the projector's brightness parameter from 70% to 80% of the basic configuration according to the preset adjustment rules.

[0034] In one possible implementation, the basic device parameter configuration information is dynamically adjusted based on the scene feature vector to construct the multimedia device operating parameter rules. Step S250 further includes step S251, which involves parsing the basic device parameter configuration information, determining the adjustable range of parameters, performing device control analysis, and setting control constraints. Specifically, for each multimedia device's basic parameters, the adjustable range is determined based on the device's technical specifications and actual operating requirements. For example, the adjustable range for a projector's brightness parameter is 10%-100%; the adjustable range for a speaker's volume parameter is 0-100 decibels. Simultaneously, control constraints are set based on the device's safe operation requirements and the specific limitations of the scene. These constraints include inter-device linkage limitations, such as preventing the lighting system from undergoing large brightness changes simultaneously when the projector's brightness is adjusted to avoid excessive visual impact on the user; and device-specific operating limitations, such as preventing certain parameters from being adjusted to their extreme values ​​after prolonged operation to ensure the device's lifespan.

[0035] Step S252: Extract the data mapping relationship between the scene feature vector and the basic device parameter configuration information according to the scene-device association database. Specifically, the data mapping relationship can be a rule pre-defined based on a large amount of experimental data or expert experience. For example, when the scene feature vector indicates strong ambient light, the mapping relationship between it and the projector brightness parameter can be: for every 100 lumens increase in ambient light intensity, the projector brightness needs to increase by 5%. For audio systems, a similar mapping relationship exists between the sound noise level in the scene feature vector and the volume parameter. These data mapping relationships are obtained by querying relevant records in the database.

[0036] Step S253: Adjust and balance the basic equipment parameter configuration information according to the data mapping relationship to generate an adjustable parameter set, which includes parameter adjustment amount and parameter adjustment direction. Specifically, based on the data mapping relationship extracted in step S252, adjust and balance the basic equipment parameter configuration information, including analyzing the combined influence of multiple factors, such as the collaborative working effect between devices and the overall experience requirements of the scenario. For each adjustable parameter, determine its adjustment amount and adjustment direction. The adjustment amount is a specific value calculated based on the data mapping relationship, and the adjustment direction indicates whether the parameter is increased or decreased. For example, according to the data mapping relationship, if the projector brightness needs to be increased by 15%, then the adjustment amount is 15%, and the adjustment direction is increase. Simultaneously, analyze potential parameter conflicts or unreasonable situations during the adjustment process, perform balancing processing, and generate an adjustable parameter set.

[0037] Step S254: Based on the control constraints, and combining the parameter adjustment amount and the parameter adjustment direction, multi-objective optimization is performed to construct a device parameter adjustment scheme. Specifically, based on the control constraints set in step S251, and combining the parameter adjustment amount and direction in the adjustable parameter set generated in step S253, multi-objective optimization is performed, i.e., optimizing multiple objective functions, such as device operating efficiency, user experience, and device lifespan. By establishing a mathematical model, optimization algorithms are used to find the optimal parameter adjustment scheme that achieves the best results for multiple objective functions while satisfying the control constraints. This scheme integrates the mutual influence and overall effect between various adjustable parameters, ensuring that the device achieves its best operating state after parameter adjustment.

[0038] Step S255: Execute the device parameter adjustment scheme for simulation verification, obtain the parameter adjustment effect, revise the device parameter adjustment scheme, and construct the multimedia device operating parameter rules. Specifically, execute the device parameter adjustment scheme generated in step S254 and perform simulation verification in a virtual environment. Using computer simulation technology, simulate the operation of a group of multimedia devices in a real-world scenario according to the adjusted parameters, observe the device operating status, parameter changes, and the overall effect of the scene. Through simulation verification, obtain data on the parameter adjustment effect, such as device response time, energy consumption changes, and scene audiovisual quality scores. Based on the simulation results, revise the device parameter adjustment scheme. If the simulation results show that the response time of a certain device is too long, the parameter adjustment amount and direction of that device can be appropriately adjusted; if the scene audiovisual quality score is low, the data mapping relationship can be re-analyzed and the balance adjusted to optimize the parameter adjustment scheme. After multiple revisions, the final multimedia device operating parameter rules are constructed.

[0039] In one possible implementation, the device parameter adjustment scheme is executed for simulation verification. The effect of the parameter adjustment is obtained, and the device parameter adjustment scheme is corrected to construct the operating parameter rules for the multimedia device. Step S255 further includes step S2551, performing digital twin simulation based on the target scene type to construct simulation scene parameters. Specifically, based on the target scene type, highly realistic simulation scene parameters are constructed using digital twin technology. Digital twin technology simulates various characteristics of the actual scene by creating virtual models of multimedia devices and scene environments. For different target scene types, such as conference rooms, home theaters, and classrooms, their unique physical parameters, environmental parameters, and equipment layout parameters are collected. For example, a conference room scene requires collecting physical parameters such as room size, wall reflectivity, and seating distribution, as well as environmental parameters such as current ambient temperature and humidity; simultaneously, the positions and connections of multimedia devices such as projectors, speakers, and microphones are determined. Based on this data, a three-dimensional virtual scene is constructed using modeling software, and each element in the scene is assigned corresponding attributes and parameters to form complete simulation scene parameters.

[0040] Step S2552 involves mapping the device parameter adjustment scheme to the simulation scene parameters for digital twin simulation monitoring to obtain device simulation results. These results include device simulation response data and device performance indicators. Specifically, each parameter in the device parameter adjustment scheme is mapped to the simulation scene parameters constructed in step S2551 through a data interface and mapping rules. The device operation simulation is then initiated in the digital twin simulation environment to monitor the device's operating status and performance in real time. During monitoring, simulation response data of the device is collected, such as the brightness change response time of the projector and the volume adjustment response time of the audio system. Simultaneously, device performance indicators are recorded, such as the projector's resolution and contrast ratio, and the audio system's distortion rate and signal-to-noise ratio. These data are acquired and stored in real time within the simulation environment using sensors and monitoring software.

[0041] Step S2553: Compare and analyze the device simulation response data with the expected operating target values ​​according to the device performance indicators, and calculate the parameter adjustment effect. The parameter adjustment effect includes adjustment deviation values ​​for multiple optimization targets. Specifically, based on the device performance indicators, compare and analyze the device simulation response data with the pre-set expected operating target values. The expected operating target values ​​are determined according to the target scenario type and user needs. For example, for a projector in a conference room scenario, the expected brightness response time is no more than 1 second, and the resolution is 1920×1080 or higher; for a speaker, the expected volume response time is no more than 1 second, the distortion rate is less than 1%, and the signal-to-noise ratio is higher than 75dB. By calculating the difference between the device simulation response data and the expected operating target values, adjustment deviation values ​​for multiple optimization targets are obtained. The adjustment deviation values ​​reflect the gap between the effect of the device parameter adjustment scheme in actual simulation and the expected targets.

[0042] Step S2554: Based on the adjustment deviation values ​​of the multiple optimization objectives, the device parameter adjustment scheme is iteratively corrected to construct the multimedia device operating parameter rules. Specifically, based on the adjustment deviation values ​​of the multiple optimization objectives calculated in step S2553, an iterative optimization algorithm is used to correct the device parameter adjustment scheme. In each iteration, the parameter values ​​in the device parameter adjustment scheme are adjusted according to the adjustment deviation value, and then digital twin simulation monitoring is performed again to obtain new device simulation results and adjustment deviation values. Through continuous iteration, the adjustment deviation value is gradually reduced, making the device parameter adjustment scheme closer to the expected operating target value. When the adjustment deviation value meets the preset convergence condition, such as the absolute value of all adjustment deviation values ​​being less than a set threshold, the iteration stops, and the device parameter adjustment scheme at this time is the final multimedia device operating parameter rule.

[0043] Step S300: Perform centralized control of the multimedia device group according to the multimedia device operating parameter rules and the target scene type, and set the first centralized control command.

[0044] Specifically, the central control platform generates the first centralized control command based on the obtained operating parameter rules of the multimedia devices and the target scenario type. This first centralized control command is a set of instructions used to control the operation of the multimedia device group, containing the specific operations and parameter settings that each device needs to perform. The command uses a unified communication protocol format and is sent to each device in the multimedia device group via wired or wireless network. To ensure accurate transmission and reception of the commands, a reliable communication connection is established between the central control platform and the multimedia devices, and technologies such as data verification and retransmission mechanisms are used to ensure communication quality.

[0045] In one possible implementation, the multimedia device group is centrally controlled according to the multimedia device operating parameter rules and the target scene type, and a first centralized control command is set. Step S300 further includes step S310, which involves identifying the multimedia device group according to the multimedia device operating parameter rules to determine multiple device control targets. Specifically, based on the multimedia device operating parameter rules, device identification technology is used to identify each device in the multimedia device group. For example, identification can be performed using the device's unique identifier or characteristic parameters. During the identification process, the acquired device information is matched with the preset device parameters in the multimedia device operating parameter rules to determine the operating parameter targets that each device needs to achieve in the current scene, thereby determining multiple device control targets. For example, for a projector device, the required brightness, contrast, and resolution parameters are identified according to the operating parameter rules; for an audio device, the required volume, tone, and sound effect modes are identified.

[0046] Step S320 involves performing device collaboration analysis based on the multimedia device group and setting device collaboration constraints. Specifically, this involves analyzing the collaboration between devices in the multimedia device group, i.e., analyzing the mutual influence and dependencies between devices. For example, the display effect of a projector is affected by the lighting system, and the volume and sound quality of speakers are affected by ambient noise and interference from other audio devices. By analyzing these relationships, device collaboration constraints are set, including the startup order of devices, the order of parameter adjustments, and the limits on the magnitude of parameter adjustments. These constraints can be determined using an expert system or based on historical data analysis to ensure that devices can work collaboratively and avoid conflicts or adverse effects.

[0047] Step S330: Perform multi-scene scheduling impact analysis according to the target scene type to generate a scene scheduling impact sequence. Specifically, according to the target scene type, analyze the impact of switching between different scenes on the multimedia device group, that is, analyze the state changes of devices, parameter adjustment requirements, and possible conflicts during scene switching. For example, when switching from a meeting scene to a presentation scene, the projector needs to switch to different display modes, and the audio system needs to adjust the volume and sound effect modes. By establishing a scene model and a device state model, simulate the scene switching process and generate a scene scheduling impact sequence. This sequence records the devices involved in each scene switching step, the operations that the devices need to perform, and the time sequence of the operations.

[0048] Step S340: Perform control analysis on the multimedia device group based on the scene scheduling influence sequence to determine device control priorities. Specifically, based on the scene scheduling influence sequence generated in step S330, perform control analysis on the multimedia device group to analyze the importance and urgency of device operations and the dependencies between devices, and determine device control priorities. For example, key devices that affect the scene display effect, such as projectors, should be given higher control priorities; some auxiliary devices, such as microphones, can be given lower control priorities if they do not affect the basic presentation. Decision analysis methods such as the analytic hierarchy process (AHP) or fuzzy comprehensive evaluation method can be used to determine device control priorities.

[0049] Step S350: The multimedia device group is centrally controlled according to the device coordination constraints, device control priorities, and multiple device control objectives, generating the first centralized control instruction. Specifically, the multimedia device group is centrally controlled by combining the device coordination constraints set in step S320, the device control priorities determined in step S340, and the multiple device control objectives determined in step S310. Control instructions are sent sequentially to each device according to the device control priorities, while ensuring that the operations between devices comply with the device coordination constraints. During the sending of control instructions, the response status of the devices is monitored in real time, and the control instructions are adjusted according to the actual feedback from the devices to ensure that the devices can accurately achieve the control objectives. Finally, the first centralized control instruction is generated, which contains the specific operation information, operation sequence, and time requirements of all devices that need to be controlled.

[0050] Step S400: Establish a communication connection between the multimedia device group and the central control platform, construct a device topology diagram, verify the first centralized control command based on the device topology diagram, and obtain the control status information of the multimedia device group.

[0051] Specifically, after the multimedia device group establishes a communication connection with the central control platform, the central control platform uses network topology discovery technology to construct a device topology map. The device topology map is a graphical representation that shows the physical connections and logical hierarchy between the various devices in the multimedia device group. Based on the device topology map, the central control platform verifies the first centralized control command, i.e., it checks and tests to ensure that the command can be executed correctly in the multimedia device group without causing damage or abnormal states to the devices. The verification process includes checking whether the command can correctly reach the target device, whether the current state of the device allows the execution of the command, and whether the state of the device after the command is executed meets expectations. By simulating command execution or actually sending test commands, the control status information of the multimedia device group is obtained. This control status information reflects the actual operating status and parameter information of each device after receiving the control command, such as the device's on / off status, current operating parameters, and fault information.

[0052] In one possible implementation, a communication connection is established between the multimedia device group and the central control platform to construct a device topology map. Step S400 further includes step S410, which involves traversing the multimedia device group to assign identifiers and setting multiple device identifiers. The central control platform automatically searches the multimedia device group according to the multiple device identifiers to construct an identifier-device mapping relationship. Specifically, an identifier assignment algorithm is used to traverse the multimedia device group, generating a unique device identifier for each device based on factors such as device type, model, and access order. For example, for projector devices, identifiers can be generated in the format "PROJ-[access sequence number]", such as "PROJ-001"; for audio devices, the format "AUDIO-[access sequence number]", such as "AUDIO-002", is used. The central control platform broadcasts search requests within the local area network according to a preset search protocol. After receiving the search request, the multimedia devices return their device identifiers to the central control platform. Upon receiving these identifiers, the central control platform maps them one-to-one with the searched devices, constructs an identifier-device mapping relationship, and stores this relationship in a database.

[0053] Step S420: Perform bidirectional authentication between the multimedia device group and the central control platform according to the identifier-device mapping relationship to establish a secure communication connection. Specifically, based on the identifier-device mapping relationship, the central control platform and the multimedia device group perform bidirectional authentication. Specifically, the central control platform first sends an authentication request to the multimedia devices, containing the device's identifier and authentication key. After receiving the authentication request, the multimedia device verifies the legitimacy of the central control platform and simultaneously decrypts and verifies the authentication key using its own private key. If the verification is successful, the multimedia device sends an authentication response to the central control platform, containing information such as the device's public key. After receiving the response, the central control platform verifies the legitimacy of the multimedia device, completing the bidirectional authentication process. After successful bidirectional authentication, the central control platform and the multimedia devices negotiate and establish a secure communication protocol, such as the SSL / TLS protocol. Through this protocol, the communication data between the two parties is encrypted and decrypted to ensure the security and integrity of the data during transmission, thereby establishing a secure communication connection.

[0054] Step S430: Based on the established secure communication connection, network probing is performed on the multimedia device group to construct a network topology. Specifically, based on the established secure communication connection, the central control platform uses network probing tools, such as Ping and Traceroute, to perform network probing on the multimedia device group. The Ping command is used to detect the network connectivity of devices by sending ICMP echo request packets to the devices and waiting for the devices to return echo response packets to determine whether the devices are online. The Traceroute command is used to probe the network paths between devices by sending IP packets with different TTL values ​​and recording the router information traversed by the packets, thereby constructing the network topology between devices. The central control platform organizes and analyzes the information obtained from the network probing to determine the location of each device in the network and the connection relationships between devices. For example, it determines which devices are in the same subnet, the data transmission paths between devices, etc., and finally constructs a network topology diagram, which is stored in the system in graphical or data structure form.

[0055] Step S440: Retrieve the physical locations of the multimedia equipment group to perform equipment dependency analysis and determine the functional dependencies between the equipment. Specifically, retrieve the physical location data of the multimedia equipment group, including the floor, room number, and specific coordinates of the equipment, through the facility management system or pre-entered equipment installation information. Analyze the functional dependencies between the equipment based on their functions and operating logic. For example, the normal display of a projector requires the cooperation of a lighting system; excessively bright light will affect the projection effect. Therefore, there is a functional dependency between the projector and the lighting system. The audio output of the audio system needs to be synchronized with the video playback device; there is also a functional dependency between them. These dependencies can be determined through expert experience, equipment manuals, or analysis of equipment operating data.

[0056] Step S450: Construct the device topology graph by using the physical locations of the multimedia device group as nodes, the network topology relationships as connecting edges of the nodes, and the device functional dependencies as edge weights. Specifically, the physical locations of the multimedia device group are used as nodes, with each node representing a multimedia device. The network topology relationships are used as connecting edges of the nodes to represent the network connections between devices. The device functional dependencies are used as edge weights, and the edge weight values ​​can be quantified according to the degree of dependency; for example, strong dependencies can be assigned higher weight values, and weak dependencies can be assigned lower weight values. Using a graphics drawing tool, a device topology graph is constructed based on the determined nodes, edges, and edge weights. This topology graph shows the physical locations, network connections, and functional dependencies between the multimedia device group.

[0057] In one possible implementation, the first centralized control command is verified based on the device topology diagram to obtain control status information of the multimedia device group. Step S400 further includes step S460, which involves performing control analysis on the multimedia device group based on the first centralized control command to determine device control propagation requirement parameters. Specifically, the first centralized control command is parsed to determine the specific multimedia device operation type targeted by the command, such as turning the device on or off, adjusting device parameters, or switching device operating modes. Simultaneously, the requirements for collaborative operation between different devices are analyzed. Based on the results of the control analysis, device control propagation requirement parameters are determined, including command propagation priority, propagation delay requirements, and propagation range.

[0058] Step S470: Based on the physical locations of the multimedia device group and the device control propagation requirement parameters, a centralized control calculation is performed by traversing the device topology map to determine the command propagation path. Specifically, based on the physical locations of the multimedia device group and combined with the device control propagation requirement parameters, a starting node is selected from the device topology map, such as the device closest to the control source or the device most critical to the control response. Then, a breadth-first search or depth-first search is performed to traverse the device topology map. During the traversal, the network connection relationships and functional dependencies between devices are analyzed, and device nodes that meet the requirements are selected according to the device control propagation requirement parameters to gradually construct the command propagation path.

[0059] During the traversal process, centralized control calculations are performed based on factors such as communication bandwidth and processing capabilities between devices. For example, if a device has low communication bandwidth, the amount of data sent to that device simultaneously needs to be appropriately delayed or reduced when transmitting instructions to ensure that instructions can be transmitted accurately and in a timely manner. At the same time, the execution order of instructions is arranged according to the processing capabilities of the devices to avoid lag or errors caused by the devices being unable to process the data.

[0060] Step S480: Control conflict detection is performed based on the command propagation path. The command propagation path is then updated in reverse based on the control conflict data to generate an optimized command propagation path. Specifically, control conflict detection is performed on the multimedia device group based on the command propagation path. The detection includes operational conflicts between devices, such as two commands simultaneously requiring a device to perform opposite operations; resource conflicts, such as multiple devices simultaneously requesting limited network bandwidth or storage resources; and time conflicts, i.e., unreasonable execution time scheduling of different commands, causing devices to fail to complete operations on time. A conflict detection model can be established to simulate and analyze device operations along the command propagation path to identify potential conflict points.

[0061] Based on the data obtained from control conflict detection, the command propagation path is updated in reverse. For devices with operational conflicts, the command propagation order is adjusted to ensure that the devices can receive and execute commands in the correct sequence. For resource conflicts, the timing of command propagation is optimized to avoid multiple devices requesting resources simultaneously. For time conflicts, the execution time of commands is rescheduled to meet the operational requirements of the devices. Through adjustment and optimization, an optimized command propagation path is generated.

[0062] Step S490: Execute the first centralized control command according to the optimized command propagation path to perform control verification and obtain the control status information of the multimedia device group. Specifically, according to the generated optimized command propagation path, the first centralized control command is sequentially sent to each device in the multimedia device group. During command propagation, the response status of the devices is monitored in real time, including whether the device successfully receives the command and whether the command is executed correctly. The control status of the devices can be determined by the feedback information returned by the devices. For example, after successfully executing the command, the device will return an acknowledgment signal. If no acknowledgment signal is received or an error signal is received, it indicates that there may be a problem with the device. Collect the feedback information from all devices, organize and analyze it to obtain the control status information of the multimedia device group.

[0063] In one possible implementation, the first centralized control instruction is executed according to the instruction propagation optimization path for control verification to obtain the control status information of the multimedia device group. Step S490 further includes step S491, matching the first centralized control instruction with the multimedia device group based on the instruction propagation optimization path to determine the device transmission sequence. Specifically, the specific content of the first centralized control instruction is parsed to determine the specific multimedia devices it includes, and the various operational requirements in the instruction are matched with the functional characteristics of the corresponding devices. For example, if the instruction requires adjusting the screen brightness, it is matched to a projector device with brightness adjustment function. Based on the instruction propagation optimization path, combined with factors such as the physical location of the devices, network connection status, and dependencies between devices, the device transmission sequence is determined. For devices with sequential operation dependencies, such as turning on the lights to create a suitable environment before turning on the projector to display the screen, it is necessary to ensure that the lighting devices receive the instruction before the projector devices. At the same time, network bandwidth is reasonably allocated to avoid network congestion caused by multiple devices receiving a large amount of data simultaneously, and the order in which devices receive instructions is arranged according to network conditions and device priority.

[0064] Step S492: Perform instruction propagation analysis on the first centralized control instruction according to the device transmission sequence, and set the instruction distribution timing. Specifically, for each device in the device transmission sequence, analyze the propagation process of the first centralized control instruction on it. Simultaneously analyze factors such as the device's processing power, the complexity of the instruction, and the device's current operating status. For example, server-level devices with strong processing power can receive and process complex instructions quickly; simpler terminal devices require a more concise instruction transmission method. Based on the results of the instruction propagation analysis, set an instruction distribution time point for each device to ensure that the device has sufficient time to receive, parse, and execute instructions, while avoiding instruction interference between devices. A time-slice rotation method can be used to allocate different time slices to different devices to receive instructions, ensuring the orderly distribution of instructions.

[0065] Step S493: Distribute the first centralized control command to the multimedia device group according to the command distribution sequence for real-time monitoring to obtain real-time transmission status information. Specifically, the first centralized control command is distributed to each device in the multimedia device group according to the set command distribution sequence. During the command distribution process, a real-time monitoring mechanism is established to track the transmission status of the command through feedback information returned by the devices. Network monitoring tools can be used to monitor the transmission of commands in the network in real time, such as the sending and receiving of data packets, transmission delay, etc. Simultaneously, the device provides real-time feedback on the command reception and processing status, such as whether the command was successfully received and the command execution progress. Feedback information from the network and devices is collected, organized, and analyzed to obtain real-time transmission status information, including the command transmission success rate, transmission delay time, device response time, and error information during command execution.

[0066] Step S494: Based on the real-time transmission status information, perform multi-dimensional analysis on the multimedia device group to generate multi-dimensional instruction execution effects. Specifically, based on the real-time transmission status information, analyze the multimedia device group from multiple dimensions such as device performance, instruction execution progress, and network status. For the device performance dimension, analyze whether the device's processing speed, response time, and other indicators meet expectations; for the instruction execution progress dimension, check whether each device executes instructions according to the predetermined plan, and whether there are any delays or early completions; for the network status dimension, focus on network latency, packet loss rate, and other issues during instruction transmission.

[0067] Based on the results of multi-dimensional analysis, the execution effect of the first centralized control commands in the multimedia device group is comprehensively evaluated. A quantitative scoring method can be used, setting corresponding weights and scoring criteria for each dimension to calculate the overall score of command execution effect.

[0068] Step S495: Based on the execution effect of the multi-dimensional instructions, the first centralized control instructions are verified to construct a device health profile. Specifically, the first centralized control instructions are verified according to the execution effect of the multi-dimensional instructions to check whether the instructions have achieved the expected control objectives, such as whether the devices are turned on as required, whether the parameters are adjusted to appropriate values, and whether the collaborative work between devices is normal. If it is found that the instruction execution effect has not met expectations, it is analyzed whether the problem lies with the instructions themselves or with device malfunctions, network problems, etc. Combining the results of the control verification and the historical operating data of the devices, a device health profile is constructed for each device in the multimedia device group, including indicators such as device operating stability, failure rate, and performance degradation.

[0069] Step S496: Add the device health profile to the control status information of the multimedia device group. Specifically, integrate the various information included in the constructed device health profile, such as device operational stability, failure rate, and performance degradation, with the previously obtained control status information of the multimedia device group to enrich the content of the control status information. Store and manage the integrated information in a unified format to form a complete control status information database for the multimedia device group.

[0070] Step S500: Based on the control status information of the multimedia device group, traverse the first centralized control instruction for dynamic optimization, and construct a second centralized control instruction to perform centralized collaborative control of the multimedia device group.

[0071] Specifically, the central control platform traverses and analyzes the first centralized control command based on the control status information of the multimedia device group. By comparing the differences between the actual control status and the expected control status of the devices, optimization algorithms are used to adjust and improve the commands, generating a second centralized control command. Compared with the first centralized control command, the second centralized control command is more in line with the actual situation of the multimedia device group, enabling unified scheduling and management of multiple devices in the multimedia device group, allowing each device to work collaboratively, and achieving overall functional optimization and improvement.

[0072] In one possible implementation, the first centralized control instructions are dynamically optimized based on the control status information of the multimedia device group, and a second centralized control instruction is constructed to perform centralized collaborative control of the multimedia device group. Step S500 further includes step S510, which involves classifying the execution of the first centralized control instructions based on the control status information of the multimedia device group to obtain multiple device control status classes. Specifically, the first centralized control instructions are classified based on the control status information of the multimedia device group. For example, if the device feedback indicates that the instruction has been fully executed and achieved the expected effect, it is classified as a successful execution class; if the device only executes part of the operation in the instruction, such as an audio device only adjusting the volume but not switching the sound effect mode, it is classified as a partial execution class; if the device feedback indicates that the instruction cannot be executed, and error messages such as "instruction format error" or "device does not support this function" appear, it is classified as an execution failure class; if the device does not provide any feedback within a specified time, it is classified as a timeout non-response class. By writing a classification algorithm program, the control status information and the first centralized control instructions are compared and analyzed one by one to identify the execution status of the instructions and classify them into the corresponding categories.

[0073] Step S520: Store and record the multiple device control status classes according to their execution time sequence to construct a status information database. Specifically, determine the execution time sequence of each device control status class based on the sending time of the first centralized control instruction and the device's feedback time. For example, for instructions transmitted over a network, record the timestamp of the instruction sending and the timestamp of the device feedback, and determine the instruction's execution time by calculating the difference between the two. A database management system, such as a relational or non-relational database, is used to store and record the multiple device control status classes according to their execution time sequence. Design a database table structure including fields such as device identifier, instruction identifier, execution status category, and execution time. Simultaneously, establish a database index to improve data retrieval speed.

[0074] Step S530: Traverse the state information database and compare it with the expected execution state information to identify abnormal execution device parameters. Specifically, based on the application scenario and preset control objectives of the multimedia device group, the expected execution state information is determined. For example, in a smart conference room, it is expected that the projector will display normally, the lighting brightness will be moderate, the sound effects will meet the meeting requirements, and the video conferencing system will start normally at the start of the meeting. This expected state information is stored in the system in advance as a comparison benchmark. Traverse the state information database and compare the actual execution state of each device control state class with the expected execution state information one by one to identify device parameters whose actual execution state is inconsistent with the expected state, i.e., abnormal execution device parameters.

[0075] Step S540: Based on the target scene type and the control state information of the multimedia device group, perform scene change analysis on the multimedia device group to obtain a scene change dataset. Specifically, based on the target scene type and the control state information of the multimedia device group, analyze scene changes, including dynamic adjustments of devices, the addition of new devices, or the removal of old devices. For example, during a theater performance, as the plot develops, it is necessary to adjust the color and brightness of stage lights, the volume and sound effects of the audio, etc., all of which are scene changes. By establishing a scene change model and processing the control state information, a scene change dataset is obtained, containing information such as device identifiers, parameter change values, and change times.

[0076] Step S550: According to the scene change dataset, map the abnormal device parameters to the first centralized control instructions to extract invalid control instructions. Specifically, establish a mapping relationship between abnormal device parameters and the first centralized control instructions. By analyzing the status information database and the scene change dataset, determine which or more first centralized control instructions caused each abnormal device parameter. For example, if the light brightness parameter is abnormal, querying the records reveals a problem with the execution of the light brightness adjustment instruction, thus mapping the abnormal light brightness parameter to that instruction. Based on the mapping relationship, extract instructions related to the abnormal device parameters from the first centralized control instructions; these instructions are the invalid control instructions. Invalid control instructions may fail to execute normally or produce unexpected results due to reasons such as incorrect instruction format, device incompatibility, or the instruction no longer being applicable after scene changes.

[0077] Step S560: Adjust the device response according to the invalid control command. Optimize the command response by iterating through the first centralized control commands based on the device adjustment parameters, and construct the second centralized control command. Specifically, for the device parameters involved in the invalid control command, adjust the device response based on the scene change dataset and the device's performance characteristics. For example, if the audio volume adjustment command is invalid, recalculate a suitable volume value based on the performance scene's requirement to increase the volume, and send an adjustment command to the audio equipment to achieve the expected volume effect. Based on the device adjustment parameters, iterate through the first centralized control commands, optimize the relevant commands, modify parameter values, command formats, or add necessary conditional judgments to improve the command response accuracy and execution efficiency. For example, if it is found that the projector resolution adjustment command is prone to failure in a specific network environment, the command format can be optimized, and network status detection and retry mechanisms can be added. Integrate the optimized commands to construct the second centralized control command. The second centralized control command can better adapt to the current state and target scene requirements of the multimedia device group, realizing centralized collaborative control of the devices.

[0078] This application employs a method that automatically detects multimedia device cluster scenes, acquires scene status data, and uploads it to a central control platform. The central control platform identifies the scene and determines the target type, obtains device operating parameter rules through scene mapping, sets a first centralized control command based on the rules and target scene type, establishes a device topology map by connecting the device cluster to the central control platform, verifies the first centralized control command to obtain control status information, dynamically optimizes the first centralized control command based on the control status information, and constructs a second centralized control command for centralized collaborative control. This method solves the technical problem of existing centralized control of multimedia device clusters, which is difficult to achieve efficient and accurate collaborative control of devices based on dynamic scene changes, and achieves the technical effect of efficient and accurate collaborative control of devices based on dynamic scene changes.

[0079] In the above text, refer to Figure 1 A multimedia device cluster centralized control method for multi-scenario scheduling according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 This invention describes a centralized control system for multi-scenario scheduling of multimedia devices according to an embodiment of the present invention.

[0080] The multimedia device cluster centralized control system for multi-scene scheduling according to embodiments of the present invention addresses the technical problem of existing multimedia device cluster centralized control systems, which struggle to efficiently and accurately perform coordinated device control based on dynamic scene changes. It achieves the technical effect of efficiently and accurately performing coordinated device control based on dynamic scene changes. The multimedia device cluster centralized control system for multi-scene scheduling includes: a scene detection module 10, a scene mapping module 20, a first centralized control instruction setting module 30, a control verification module 40, and an instruction optimization module 50.

[0081] Scene detection module 10 is used to automatically detect scenes of the multimedia device group and upload scene status data to the central control platform; scene mapping module 20 is used to identify scenes through the central control platform, determine the target scene type, perform scene mapping according to the target scene type, and obtain multimedia device operating parameter rules; first centralized control instruction setting module 30 is used to centrally control the multimedia device group according to the multimedia device operating parameter rules and the target scene type, and set the first centralized control instruction; control verification module 40 is used to establish a communication connection between the multimedia device group and the central control platform, construct a device topology map, perform control verification of the first centralized control instruction based on the device topology map, and obtain control status information of the multimedia device group; instruction optimization module 50 is used to dynamically optimize the first centralized control instruction according to the control status information of the multimedia device group, construct a second centralized control instruction for centralized collaborative control of the multimedia device group.

[0082] The scene mapping module 20 is described in detail below: As mentioned above, the central control platform is used to identify the scene, determine the target scene type, and perform scene mapping according to the target scene type to obtain the multimedia device operating parameter rules. The scene mapping module 20 may further include: a time-frequency domain feature analysis unit for performing time-frequency domain feature analysis on the scene state data through the central control platform to construct a scene feature vector; a distribution calculation unit for performing feature transformation based on the scene feature vector using a multi-layer neural network, mapping the feature transformation result to the scene of the multimedia device group for distribution calculation to obtain scene type probability distribution parameters; a hybrid classification unit for performing hybrid classification according to the scene type probability distribution parameters to generate a scene type identification result, the scene type identification result including the target scene type; a retrieval and query unit for constructing a scene-device association database, mapping the target scene type as an index to the scene-device association database for retrieval and query to extract basic device parameter configuration information; and a dynamic adjustment unit for dynamically adjusting the basic device parameter configuration information based on the scene feature vector to construct the multimedia device operating parameter rules.

[0083] The dynamic adjustment unit, which dynamically adjusts the basic equipment parameter configuration information based on the scene feature vector to construct the multimedia equipment operating parameter rules, may further include: a control constraint setting subunit for parsing the basic equipment parameter configuration information, determining the adjustable range of parameters, performing equipment control analysis, and setting control constraints; a data mapping relationship extraction subunit for extracting the data mapping relationship between the scene feature vector and the basic equipment parameter configuration information according to the scene-equipment association database; an adjustment balance analysis subunit for performing adjustment balance analysis on the basic equipment parameter configuration information according to the data mapping relationship, generating an adjustable parameter set, which includes parameter adjustment amount and parameter adjustment direction; a multi-objective optimization subunit for performing multi-objective optimization according to the control constraints, combined with the parameter adjustment amount and the parameter adjustment direction, to construct a device parameter adjustment scheme; and a simulation verification subunit for executing the device parameter adjustment scheme to perform simulation verification, obtaining parameter adjustment effects, correcting the device parameter adjustment scheme, and constructing the multimedia equipment operating parameter rules.

[0084] The simulation verification subunit may further include: a digital twin simulation component for performing digital twin simulation based on the target scene type to construct simulation scene parameters; a digital twin simulation monitoring component for mapping the device parameter adjustment scheme to the simulation scene parameters to perform digital twin simulation monitoring and obtain device simulation results, which include device simulation response data and device performance indicators; a parameter adjustment effect calculation component for comparing and analyzing the device simulation response data with the expected operating target value according to the device performance indicators to calculate the parameter adjustment effect, which includes adjustment deviation values ​​of multiple optimization targets; and an iterative correction component for iteratively correcting the device parameter adjustment scheme based on the adjustment deviation values ​​of the multiple optimization targets to construct the multimedia device operating parameter rules.

[0085] The detailed description of the specific configuration of the first centralized control instruction setting module 30 is explained as follows: As described above, the multimedia device group is centrally controlled according to the multimedia device operating parameter rules and the target scene type, and a first centralized control instruction is set. The first centralized control instruction setting module 30 may further include: a device identification unit for identifying devices in the multimedia device group according to the multimedia device operating parameter rules and determining multiple device control targets; a device collaboration analysis unit for performing device collaboration analysis based on the multimedia device group and setting device collaboration constraints; a multi-scene scheduling impact analysis unit for performing multi-scene scheduling impact analysis according to the target scene type and generating a scene scheduling impact sequence; a control analysis unit for performing control analysis on the multimedia device group according to the scene scheduling impact sequence and determining device control priorities; and a centralized control unit for centrally controlling the multimedia device group according to the device collaboration constraints, the device control priorities, and the multiple device control targets, and generating the first centralized control instruction.

[0086] The detailed description of the specific configuration of the control verification module 40 is explained as follows: As mentioned above, to establish a communication connection between the multimedia device group and the central control platform and construct a device topology graph, the control verification module 40 may further include: an identifier allocation unit for traversing the multimedia device group to allocate identifiers, setting multiple device identifiers, and the central control platform automatically searching the multimedia device group according to the multiple device identifiers to construct an identifier-device mapping relationship; a two-way authentication unit for performing two-way authentication between the multimedia device group and the central control platform according to the identifier-device mapping relationship to construct a secure communication connection relationship; a network detection unit for performing network detection on the multimedia device group based on the secure communication connection relationship to construct a network topology relationship; a device dependency analysis unit for retrieving the physical location of the multimedia device group to perform device dependency analysis and determine device functional dependencies; and a device topology graph construction unit for using the physical location of the multimedia device group as nodes, the network topology relationship as the connection edge of the node, and the device functional dependency relationship as the edge weight to construct the device topology graph.

[0087] The control verification module 40 may further include: a device control propagation requirement parameter determination unit for performing control analysis on the multimedia device group based on the first centralized control command to determine device control propagation requirement parameters; a centralized control calculation unit for performing centralized control calculations by traversing the device topology map according to the physical location of the multimedia device group and the device control propagation requirement parameters to determine the command propagation path; a control conflict detection unit for performing control conflict detection based on the command propagation path, updating the command propagation path in reverse according to the control conflict data, and generating an optimized command propagation path; and a control verification unit for executing the first centralized control command according to the optimized command propagation path to perform control verification and obtain the control status information of the multimedia device group.

[0088] The control verification unit further includes: a matching subunit for matching the first centralized control instruction with the multimedia device group based on the instruction propagation optimization path to determine the device transmission sequence; an instruction propagation analysis subunit for performing instruction propagation analysis on the first centralized control instruction according to the device transmission sequence and setting the instruction distribution timing; a real-time monitoring subunit for distributing the first centralized control instruction to the multimedia device group according to the instruction distribution timing for real-time monitoring and obtaining real-time transmission status information; a multi-dimensional analysis subunit for performing multi-dimensional analysis on the multimedia device group based on the real-time transmission status information and generating multi-dimensional instruction execution effects; a device health profile construction subunit for performing control verification on the first centralized control instruction based on the multi-dimensional instruction execution effects and constructing a device health profile; and a profile addition subunit for adding the device health profile to the control status information of the multimedia device group.

[0089] The detailed description of the specific configuration of the instruction optimization module 50 is as follows: As described above, the instruction optimization module 50 dynamically optimizes the first centralized control instruction based on the control status information of the multimedia device group, and constructs a second centralized control instruction for centralized collaborative control of the multimedia device group. The instruction optimization module 50 may further include: an execution classification unit for performing execution classification based on the control status information of the multimedia device group, and obtaining multiple device control status classes; a storage and recording unit for storing and recording the multiple device control status classes according to the execution time sequence, and constructing a status information database; an execution abnormal device parameter identification unit for comparing the status information database with the expected execution status information, and identifying execution abnormal device parameters; a scene change analysis unit for performing scene change analysis on the multimedia device group based on the target scene type and the control status information of the multimedia device group, and obtaining a scene change dataset; an invalid control instruction extraction unit for mapping the abnormal device parameters to the first centralized control instruction to extract invalid control instructions according to the scene change dataset; and an instruction response optimization unit for adjusting the device response according to the invalid control instructions, optimizing the instruction response based on the device adjustment parameters, and constructing the second centralized control instruction.

[0090] The multimedia device cluster centralized control system for multi-scenario scheduling provided in the embodiments of the present invention can execute the multimedia device cluster centralized control method for multi-scenario scheduling provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0091] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0092] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A centralized control method for multimedia device clusters oriented towards multi-scenario scheduling, characterized in that, The method includes: Automatically detect the scene of the multimedia device group and upload the scene status data to the central control platform; The central control platform is used to identify the target scene type, and scene mapping is performed according to the target scene type to obtain the operating parameter rules of the multimedia device. The multimedia device group is centrally controlled according to the multimedia device operating parameter rules and the target scene type, and a first centralized control command is set. Establish a communication connection between the multimedia device group and the central control platform, construct a device topology diagram, verify the first centralized control command based on the device topology diagram, and obtain the control status information of the multimedia device group. Based on the control status information of the multimedia device group, the first centralized control instruction is traversed and dynamically optimized to construct a second centralized control instruction for centralized and coordinated control of the multimedia device group.

2. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 1, characterized in that, The method involves using the central control platform to perform scene recognition, determine the target scene type, and perform scene mapping according to the target scene type to obtain multimedia device operating parameter rules. The central control platform performs time-frequency domain feature analysis on the scene status data to construct a scene feature vector. Based on the scene feature vector, feature transformation is performed according to a multi-layer neural network. The feature transformation result is mapped to the scene of the multimedia device group for distribution calculation to obtain the scene type probability distribution parameters. The scene type is classified according to the probability distribution parameters of the scene type to generate a scene type identification result, which includes the target scene type. Construct a scenario-device association database, and use the target scenario type as an index to map to the scenario-device association database for retrieval and query, and extract basic device parameter configuration information; Based on the scene feature vector, the basic equipment parameter configuration information is dynamically adjusted to construct the operating parameter rules of the multimedia equipment.

3. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 2, characterized in that, The method involves dynamically adjusting the basic equipment parameter configuration information based on the scene feature vector to construct the multimedia equipment operating parameter rules, including: Based on the basic equipment parameter configuration information, the adjustable range of parameters is determined, equipment control analysis is performed, and control constraints are set. The data mapping relationship between the scene feature vector and the basic device parameter configuration information is extracted from the scene-device association database. The basic equipment parameter configuration information is adjusted and balanced according to the data mapping relationship to generate an adjustable parameter set, which includes parameter adjustment amount and parameter adjustment direction; Based on the control constraints, and combined with the parameter adjustment amount and the parameter adjustment direction, a multi-objective optimization is performed to construct a device parameter adjustment scheme. The device parameter adjustment scheme is executed for simulation verification. The effect of parameter adjustment is obtained, the device parameter adjustment scheme is modified, and the operating parameter rules of the multimedia device are constructed.

4. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 3, characterized in that, The method includes: performing simulation verification of the device parameter adjustment scheme, obtaining the effect of parameter adjustment, revising the device parameter adjustment scheme, and constructing the operating parameter rules of the multimedia device. Based on the target scene type, perform digital twin simulation and construct simulation scene parameters; The device parameter adjustment scheme is mapped to the simulation scenario parameters for digital twin simulation monitoring to obtain device simulation results, which include device simulation response data and device performance indicators. The simulation response data of the equipment is compared and analyzed with the expected operating target value according to the equipment performance index, and the parameter adjustment effect is calculated. The parameter adjustment effect includes the adjustment deviation value of multiple optimization targets. The device parameter adjustment scheme is iteratively corrected based on the adjustment deviation values ​​of the multiple optimization objectives to construct the operating parameter rules of the multimedia device.

5. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 1, characterized in that, Centralized control of the multimedia device group is performed according to the multimedia device operating parameter rules and the target scene type, and a first centralized control command is set. The method includes: The multimedia device group is identified according to the multimedia device operating parameter rules, and multiple device control targets are determined. Based on multimedia device groups, perform device collaboration analysis and set device collaboration constraints; Perform multi-scenario scheduling impact analysis according to the target scenario type, and generate a scenario scheduling impact sequence; Based on the scene scheduling impact sequence, control analysis is performed on the multimedia device group to determine the device control priority; The multimedia device group is centrally controlled according to the device coordination constraints, the device control priority, and the multiple device control objectives, and the first centralized control instruction is generated.

6. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 1, characterized in that, Establishing a communication connection between the multimedia device group and the central control platform, and constructing a device topology diagram, includes the following methods: The multimedia device group is traversed and identifiers are assigned. Multiple device identifiers are set. The central control platform automatically searches the multimedia device group according to the multiple device identifiers to construct an identifier-device mapping relationship. The multimedia device group and the central control platform are bidirectionally authenticated according to the identifier-device mapping relationship to establish a secure communication connection. Based on the secure communication connection relationship, network detection is performed on the multimedia device group to construct the network topology relationship; The physical locations of the multimedia device group are retrieved to perform device dependency analysis and determine the functional dependencies of the devices. The device topology graph is constructed by using the physical locations of the multimedia device group as nodes, the network topology relationships as the connecting edges of the nodes, and the device functional dependencies as the edge weights.

7. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 6, characterized in that, Based on the device topology diagram, the first centralized control command is verified to obtain control status information of the multimedia device group. The method includes: Based on the first centralized control command, control analysis is performed on the multimedia device group to determine the device control propagation requirement parameters. Based on the physical location of the multimedia device group and the device control propagation requirement parameters, the device topology is traversed to perform centralized control calculations and determine the command propagation path; Control conflict detection is performed based on the command propagation path, and the command propagation path is updated in reverse according to the control conflict data to generate an optimized command propagation path; The first centralized control instruction is executed according to the instruction propagation optimization path to perform control verification and obtain the control status information of the multimedia device group.

8. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 7, characterized in that, The method involves executing the first centralized control instruction according to the optimized instruction propagation path to perform control verification and obtain the control status information of the multimedia device group. Based on the instruction propagation optimization path, the first centralized control instruction is matched with the multimedia device group to determine the device transmission sequence; The first centralized control command is analyzed for instruction propagation according to the device transmission sequence, and the instruction distribution timing is set. The first centralized control instruction is distributed to the multimedia device group according to the instruction distribution sequence for real-time monitoring to obtain real-time transmission status information. Based on the real-time transmission status information, a multi-dimensional analysis of the multimedia device group is performed to generate multi-dimensional instruction execution effects. Based on the execution effect of the multi-dimensional instructions, the first centralized control instructions are controlled and verified to construct a device health profile. Add the device health profile to the control status information of the multimedia device group.

9. The multimedia device cluster centralized control method for multi-scenario scheduling as described in claim 1, characterized in that, Based on the control status information of the multimedia device group, the first centralized control command is traversed and dynamically optimized to construct a second centralized control command for centralized and coordinated control of the multimedia device group. The method includes: Based on the control status information of the multimedia device group, the first centralized control instructions are traversed and classified for execution to obtain multiple device control status classes; The control status classes of the multiple devices are stored and recorded according to the execution time sequence to construct a status information database; The status information database is traversed and compared with the expected execution status information to identify abnormal device parameters. Based on the target scene type and the control status information of the multimedia device group, a scene change analysis is performed on the multimedia device group to obtain a scene change dataset. Based on the scenario change dataset, the abnormal device parameters are mapped to the first centralized control command to extract invalid control commands; The device response is adjusted according to the invalid control command, and the command response is optimized by traversing the first centralized control command according to the device adjustment parameters, and the second centralized control command is constructed.

10. A centralized control system for multimedia device clusters oriented towards multi-scenario scheduling, characterized in that, The system is used to implement the multimedia device cluster centralized control method for multi-scenario scheduling as described in any one of claims 1-9, and the system includes: The scene detection module is used to automatically detect the scene of the multimedia device group and upload the scene status data to the central control platform. The scene mapping module is used to identify scenes through the central control platform, determine the target scene type, perform scene mapping according to the target scene type, and obtain the operating parameter rules of the multimedia device. The first centralized control instruction setting module is used to centrally control the multimedia device group according to the multimedia device operating parameter rules and the target scene type, and to set the first centralized control instruction; The control verification module is used to establish a communication connection between the multimedia device group and the central control platform, construct a device topology diagram, perform control verification on the first centralized control command based on the device topology diagram, and obtain control status information of the multimedia device group. The instruction optimization module is used to dynamically optimize the first centralized control instruction based on the control status information of the multimedia device group, and construct a second centralized control instruction to perform centralized and coordinated control of the multimedia device group.

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