Communication control method and system for sound equipment

Abstract

The invention discloses a communication control method and system for sound equipment, and relates to the technical field of communication control methods, and a plurality of sub-communication items are determined based on detection of a communication mode of the sound equipment. And the communication control system of the sound equipment is determined according to the communication content of each sub-communication item, the corresponding communication effect coefficient and the current work task of the sound equipment, so that the accuracy of the communication control system of the sound equipment is improved. Therefore, a plurality of sub-communication optimization contents are determined according to the identification of the communication optimization event, and the dynamic communication mode of the sound equipment is determined based on the working state of the sound equipment, the communication control system and the plurality of sub-communication optimization contents. And determining the dynamic communication event of the sound equipment according to the dynamic communication mode, the load of the sound equipment and the corresponding communication scene, thereby realizing the overall consideration of the dynamic communication mode, the load of the sound equipment and the corresponding communication scene, and improving the accuracy of the dynamic communication mode of the sound equipment.

Description

Technical Field

[0001] This invention relates to the technical field of communication control methods, and more particularly to a communication control method and system for audio equipment. Background Technology

[0002] With the development of technology, audio equipment has been gradually applied to people's lives. Audio equipment is no longer a simple player and is gradually expanding towards intelligence. In the existing technology, the communication scenario of the audio equipment is collected, and the corresponding communication mode of the audio equipment is matched based on the communication scenario. However, the communication effect coefficient and the current working task of the audio equipment are ignored, which affects the accuracy of the communication control system of the audio equipment and results in low accuracy of the dynamic communication mode of the audio equipment. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a communication control method and system for audio equipment.

[0004] This invention provides a communication control method for an audio device, comprising: The database of audio equipment is determined based on the detection of audio equipment, the corresponding communication space is determined by traversing the database of audio equipment, and multiple sub-communication modules are determined based on the identification of the communication space. The communication scenario of the audio equipment is determined based on multiple environmental data and the current location of the audio equipment. The communication method of the audio equipment is determined based on the communication scenario and the communication status of multiple sub-communication modules. Based on the detection of the communication method of the audio equipment, multiple sub-communication items are determined. The communication control system of the audio equipment is determined according to the communication content of each sub-communication item, the corresponding communication effect coefficient, and the current working task of the audio equipment. In the communication control system, the communication lag event of the audio equipment is determined based on multiple communication data of the audio equipment, the response information of the audio equipment, and the communication control system. The communication optimization event is determined based on the communication lag event, the communication priority of multiple sub-communication modules, and the corresponding communication status. Based on the identification of communication optimization events, multiple sub-communication optimization contents are determined. Based on the working status of the audio equipment, the communication control system, and the multiple sub-communication optimization contents, the dynamic communication mode of the audio equipment is determined. Based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, the dynamic communication events of the audio equipment are determined.

[0005] This invention provides a communication control system for an audio device, which is applied to the aforementioned communication control method for the audio device. The communication control system for the audio device includes: The identification module is used to determine the database of audio devices based on the detection of audio devices, determine the corresponding communication space based on the traversal of the audio device database, and determine multiple sub-communication modules based on the identification of the communication space. The communication mode module is used to determine the communication scenario of the audio equipment based on multiple environmental data of the audio equipment and the current location of the audio equipment, and to determine the communication mode of the audio equipment according to the communication scenario of the audio equipment and the communication status of multiple sub-communication modules. The communication control system module is used to determine multiple sub-communication items based on the detection of the communication method of the audio equipment, and to determine the communication control system of the audio equipment according to the communication content of each sub-communication item, the corresponding communication effect coefficient and the current working task of the audio equipment. The communication optimization event module is used in the communication control system to determine the communication lag event of the audio equipment based on multiple communication data of the audio equipment, the response information of the audio equipment, and the communication control system. Based on the communication lag event, the communication priority of multiple sub-communication modules, and the corresponding communication status, the communication optimization event is determined. The dynamic communication event module is used to determine multiple sub-communication optimization contents based on the identification of communication optimization events. Based on the working status of the audio equipment, the communication control system, and the multiple sub-communication optimization contents, the dynamic communication mode of the audio equipment is determined. Based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, the dynamic communication events of the audio equipment are determined.

[0006] Compared with the prior art, the beneficial effects of the present invention are: In this embodiment of the invention, the method determines a database of audio equipment based on the detection of the audio equipment, determines a corresponding communication space based on the traversal of the audio equipment database, and determines multiple sub-communication modules based on the identification of the communication space. The communication scenario of the audio equipment is determined based on multiple environmental data of the audio equipment and its current location. The communication mode of the audio equipment is determined based on the communication scenario and the communication status of the multiple sub-communication modules. Multiple sub-communication items are determined based on the detection of the communication mode of the audio equipment. The communication control system of the audio equipment is determined based on the communication content of each sub-communication item, the corresponding communication effect coefficient, and the current working task of the audio equipment. This introduces a communication scenario of the audio equipment and further controls the communication mode of the audio equipment, taking into account the overall consideration of the communication content, corresponding communication effect coefficient, and current working task of each sub-communication item, thereby improving the accuracy of the communication control system of the audio equipment.

[0007] Therefore, in the communication control system, communication lag events of the audio equipment are determined based on multiple communication data, response information, and the communication control system. Communication optimization events are then determined based on these lag events, the communication priorities of multiple sub-communication modules, and their corresponding communication states. Multiple sub-communication optimization contents are determined based on the identification of these optimization events. The dynamic communication mode of the audio equipment is determined based on its operating state, the communication control system, and these sub-communication optimization contents. Dynamic communication events are then determined based on this dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario. By introducing communication optimization events, the dynamic communication mode is further controlled, achieving a holistic consideration of the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, thus improving the accuracy of the audio equipment's dynamic communication mode. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the communication control method for an audio device in an embodiment of the present invention. Figure 2 This is a flowchart illustrating step S11 in the communication control method for an audio device according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating step S12 in the communication control method for an audio device according to an embodiment of the present invention. Figure 4 This is a flowchart illustrating step S13 in the communication control method for an audio device according to an embodiment of the present invention. Figure 5 This is a flowchart illustrating step S14 of the communication control method for an audio device in an embodiment of the present invention. Figure 6 This is a flowchart illustrating step S15 of the communication control method for an audio device in an embodiment of the present invention. Figure 7 This is a schematic diagram of the structural composition of the communication control system of the audio equipment in an embodiment of the present invention. Detailed Implementation

[0009] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0010] Please see Figures 1 to 7 A communication control method for audio equipment, applied in a communication control scenario; the communication control method for audio equipment includes: Step S11: Determine the database of the audio equipment based on the detection of the audio equipment, determine the corresponding communication space based on the traversal of the audio equipment database, and determine multiple sub-communication modules based on the identification of the communication space; Step S12: Determine the communication scenario of the audio device based on multiple environmental data of the audio device and the current location of the audio device, and determine the communication method of the audio device according to the communication scenario of the audio device and the communication status of multiple sub-communication modules; Step S13: Based on the detection of the communication method of the audio equipment, determine multiple sub-communication items, and determine the communication control system of the audio equipment according to the communication content of each sub-communication item, the corresponding communication effect coefficient and the current working task of the audio equipment; Step S14: In the communication control system, the communication lag event of the audio equipment is determined based on multiple communication data of the audio equipment, the response information of the audio equipment and the communication control system. The communication optimization event is determined based on the communication lag event, the communication priority of multiple sub-communication modules and the corresponding communication status. Step S15: Based on the identification of communication optimization events, determine multiple sub-communication optimization contents, determine the dynamic communication mode of the audio equipment based on the working status of the audio equipment, the communication control system and the multiple sub-communication optimization contents, and determine the dynamic communication events of the audio equipment based on the dynamic communication mode, the load of the audio equipment and the corresponding communication scenario.

[0011] refer to Figure 2 In step S11, the specific steps are as follows: S111: Based on the detection of the audio equipment, the control chip of the audio equipment is marked, the database of the audio equipment is determined by tracing the control chip, and the database of the audio equipment is traversed. At this time, multiple spatial nodes are determined by traversing the database of the audio equipment, and the corresponding communication space is determined by tracing the source of each spatial node. S112: Based on the identification of the communication space, the transmission path of the communication data is determined; based on the detection of the transmission path, multiple communication nodes are determined; based on the tracing of each communication node, the corresponding sub-communication module is matched to collect multiple sub-communication modules.

[0012] In the embodiments of this application, the control chip of the audio device is marked based on the detection of the audio device, the database of the audio device is determined based on the tracing of the control chip, and the database of the audio device is traversed. At this time, multiple spatial nodes are determined based on the traversal of the database of the audio device, and the corresponding communication space is determined based on the tracing of each spatial node. This takes into account the overall consideration of the tracing of each spatial node and ensures the accuracy of the corresponding communication space.

[0013] At this point, the system identifies the core SoC on the motherboard by scanning the bus (such as I²C, SPI) or reading the register. This identifier is usually the chip's JEDECID, vendor ID, or a specific device address. After successful identification, the system will create a logical tag or handle for the chip in memory, and all subsequent operations related to the chip will be addressed through this tag.

[0014] The system uses the chip identifier obtained in the previous step to perform an index lookup in a pre-built "device capability database". This database can be a structured data table (such as an array, linked list, or hash table) in the firmware, where the key is the chip model and the value is a pointer to a structure that points to a detailed description of the chip's capabilities. This structure contains metadata such as all communication protocols supported by the chip, maximum throughput, power consumption model, and peripheral interfaces. This process ensures that the system can dynamically load software drivers and configuration parameters that are precisely matched to the hardware.

[0015] The system uses iterators or recursive functions to access each functional item in the chip capability structure loaded in the previous step one by one. For example, if the structure contains a "communication protocol list", the traversal process is to check each item in the list in turn, such as "Bluetooth 5.3", "proprietary 2.4G protocol", "Wi-Fi 802.11ac", etc. The purpose of the traversal is to completely enumerate all potential communication capabilities supported by the hardware without omitting any.

[0016] During the traversal, for each valid communication function item identified, the system creates a "space node" object in memory. This object is a data structure that encapsulates the core attributes of the function, such as: protocol type (e.g., PROTOCOL_BT), physical layer characteristics (e.g., modulation method, frequency band), quality of service requirements (e.g., default latency, bandwidth), etc. Each space node represents an independent, manageable communication resource.

[0017] The system categorizes nodes into higher-level "communication spaces" based on their attributes (such as protocol type and application scenario). A "communication space" is a logical container that manages a group of functionally related or resource-sharing "space nodes." For example, all Bluetooth-related nodes (audio, control, BLE) are categorized into the "Bluetooth communication space," while private 2.4G nodes are categorized into the "private 2.4G communication space." This hierarchical abstraction (communication space > space node) simplifies the management of complex hardware resources by upper-layer applications.

[0018] Furthermore, the transmission path of communication data is determined based on the identification of the communication space, multiple communication nodes are identified based on the detection of the transmission path, and corresponding sub-communication modules are matched based on the tracing of each communication node, so as to collect multiple sub-communication modules. This approach incorporates the overall consideration of communication space identification and ensures the accuracy of the transmission path of communication data.

[0019] At this point, the system will instantiate a protocol stack for each communication space and define the complete route of data from the application layer to the physical layer (PHY). This path describes a series of processing modules that the data packet passes through, such as: application layer data encapsulation > transport layer segmentation > data link layer (L2CAP) processing > host controller interface (HCI) commands > hardware abstraction layer (HAL) driver > radio frequency front end. The determination of this path means that the system allocates the necessary software resources and hardware interfaces for this communication space.

[0020] The system identifies key processing units and status checkpoints along the path; these are called "communication nodes." These nodes can be: protocol layer nodes (such as L2CAP channel managers), scheduling nodes (such as task queues), hardware interface nodes (such as DMA channels), or buffer nodes (such as TX / RXFIFO queues). Each node represents an observable and controllable state point in the data stream.

[0021] The system associates each "communication node" with a specific, executable software module or hardware driver based on its function and location. This "sub-communication module" is the entity responsible for the specific function of that node. For example, an "HCI command node" will be matched with an "HCI driver module"; an "RF register node" will be matched with an "RF transceiver driver module". This process completes the binding from the abstract node to the specific execution unit, providing an operation entry point for subsequent real-time control and data acquisition.

[0022] Once all sub-communication modules are matched and activated, the system establishes a monitoring framework. This framework continuously collects runtime status data from each sub-communication module through polling, interrupt callbacks, or event subscriptions. The collected data includes, but is not limited to: packet transmission and reception counts, bit error rate (BER), signal strength indicator (RSSI), link quality indicator (LQI), buffer level, CPU utilization, task scheduling latency, etc. This data forms the basis for subsequent steps of intelligent decision-making and dynamic optimization.

[0023] refer to Figure 3 In step S12, the specific steps are as follows: S121: Collect the current position of the audio equipment, determine multiple environmental data based on the environmental detection of the current position of the audio equipment, and determine the communication scenario of the audio equipment based on the multiple environmental data of the audio equipment, the current position and the overall shape of the audio equipment; S122: Determine the corresponding communication status based on the detection of multiple sub-communication modules, collect the communication status of multiple sub-communication modules, and determine the communication mode of the audio equipment according to the communication scenario of the audio equipment, the communication status of multiple sub-communication modules and the current working task of the audio equipment. In the embodiments of this application, the current position of the audio device is collected, multiple environmental data are determined based on the environmental detection of the current position of the audio device, and the communication scenario of the audio device is determined according to the multiple environmental data of the audio device, the current position and the overall shape of the audio device. This approach takes into account the overall consideration of the multiple environmental data of the audio device, the current position and the overall shape of the audio device, thus ensuring the accuracy of the communication scenario of the audio device.

[0024] At this point, the system adopts a multi-sensor fusion strategy to improve the accuracy and robustness of positioning; outdoor positioning mainly relies on the Global Navigation Satellite System (GNSS); indoor positioning is achieved through Wi-Fi scanning or Bluetooth beacons; at the same time, using accelerometer and gyroscope data in the inertial measurement unit (IMU), the attitude and motion state of the device are calculated in real time through algorithms such as Kalman filtering.

[0025] After determining the location, the system initiates a multi-dimensional environmental perception program to quantitatively analyze the physical and electromagnetic environment around the device; it performs spectrum scanning through the radio frequency front end to build a real-time "interference map"; it activates the microphone array to collect environmental audio samples and calculate acoustic parameters such as sound pressure level (SPL) and reverberation time (RT60); and it executes Bluetooth and Wi-Fi discovery processes to form a local network topology map.

[0026] The system fuses and extracts features from data from different sensors, and inputs these feature vectors into a pre-trained scene classification model (which can be a rule-based expert system or a machine learning model). The "overall form" of the device (such as portable or fixed) serves as an important prior weight, which adjusts the model's decision-making tendency and ultimately outputs one or more communication scene labels with the highest probability.

[0027] Specifically, regarding the audio equipment, which uses the ATS2835P chip, when the user moves the audio equipment from the living room to the courtyard where the party is being held, the device's IMU detects a significant acceleration and displacement process. The device initiates a Wi-Fi scan and finds a connection to a new wireless access point with the SSID "Party_Garden". The signal strength is good, but no GPS signal is detected. The system determines the current location to be "outdoor courtyard".

[0028] The ATS2835P's RF module performed a fast spectrum scan, revealing over 25 active Wi-Fi channels in the 2.4GHz band. Bluetooth broadcast packet density was extremely high, with the system calculating a channel congestion rate of 95% and an average interference intensity of -65dBm. The microphone array detected continuous background music and conversations. The DSP algorithm calculated an ambient noise SPL of 78dB and a short reverberation time RT60, indicating an open or semi-open space. The scan detected a user's mobile phone (Bluetooth classic audio source, RSSI -80dBm), several nearby guests' mobile phones, and a wireless subwoofer to be connected (private 2.4G signal, RSSI -70dBm).

[0029] The system generates a feature vector: {Location: Outdoor, Channel congestion: 0.95, Interference intensity: -65dBm, Noise level: 78dB, Movement status: Stationary}. This feature vector is input into the scene classification model. Based on strong features such as high interference, high noise, and outdoor conditions, the model classifies the current environment as a "high-interference outdoor party" scene with a 98% probability. Since the sound equipment is in the form of a "high-end sound bar (non-portable)," the system excludes the possibility of "outdoor movement" and confirms the context of "complex environment in a fixed location," further enhancing the confidence of the "high-interference outdoor party" scene.

[0030] Furthermore, the corresponding communication status is determined based on the detection of multiple sub-communication modules. The communication status of multiple sub-communication modules is collected, and the communication mode of the audio equipment is determined according to the communication scenario of the audio equipment, the communication status of multiple sub-communication modules, and the current working task of the audio equipment. This takes into account the overall consideration of the communication scenario of the audio equipment, the communication status of multiple sub-communication modules, and the current working task of the audio equipment, ensuring the accuracy of the communication mode of the audio equipment.

[0031] At this point, the system reads a set of standardized key performance indicators from the drivers and firmware of each sub-communication module matched in S112 through polling or interrupt-driven methods. These indicators constitute a "communication status" vector, including: link layer status (such as LINK_UP / DOWN), transmission quality indicators (such as RSSI, PER), performance and load indicators (such as throughput, latency), and resource usage indicators (such as CPU utilization). The acquisition process is continuous and high-frequency, forming a time-series data stream, providing real-time basis for dynamic decision-making.

[0032] The system quantifies three core inputs—communication scenario, communication status, and current task—and inputs them into a decision engine. This engine can be a rule-based expert system or a more advanced optimization algorithm. The output "communication method" is not a single action, but a complete set of configuration strategies, including: primary / backup link definition, protocol stack parameter reconfiguration, hybrid protocol stack scheduling strategy, system resource allocation, and power consumption management strategy.

[0033] Specifically, the system reads the status of each module in real time, forming the following snapshots: Bluetooth audio module: LINK_UP, RSSI=-85dBm, PER=5%, end-to-end latency=45ms (large fluctuations), L2CAP queue depth=8 / 10 (close to congestion); Private 2.4G module: LINK_UP, RSSI=-70dBm, PER=0.1%, end-to-end latency=12ms (stable), DMA buffer usage=20%; BLE control module: LINK_UP, RSSI=-82dBm, used for App control, with extremely small data volume and good status.

[0034] Input parameter fusion: Communication scenario: "High interference outdoor party" (meaning severe interference, requiring strong anti-interference strategies); Communication status: Poor Bluetooth link quality, which has become a bottleneck; Excellent private 2.4G link quality with large performance margin; Current task: The user is playing high-bitrate music on their mobile phone and requires the wireless subwoofer to provide synchronized bass effects, which is a complex task with extremely high requirements for real-time performance and stability; The decision engine infers based on the rule base: IF scenario = "high interference" AND Bluetooth status.RSSI < threshold AND private 2.4G status.latency < threshold THEN activate "cooperative anti-interference mode"; IF task = "high-quality audio playback" AND private 2.4G status.stability > Bluetooth status.stability THEN assign the highest priority to private 2.4G.

[0035] The system ultimately determined and implemented the following communication methods: "Private 2.4G priority cooperative anti-interference mode" was enabled; the hybrid protocol stack scheduler was reconfigured, and the private 2.4G data transmission and reception tasks were given the highest real-time priority, executed preemptively to ensure that their latency was always below 15ms; Bluetooth tasks were downgraded to normal priority; the "dual-mode cooperative dynamic spectrum management algorithm" was activated; the private 2.4G module actively selected the cleanest channel (such as Channel 11) and notified the Bluetooth protocol stack; the Bluetooth frequency hopping sequence was dynamically adjusted to prioritize avoiding Channel 11 and its adjacent channels, thereby achieving "cooperative avoidance" rather than "independent avoidance"; the transmit power of the private 2.4G module was adjusted to +8dBm to enhance link margin, while the transmit power of the Bluetooth module remained at the default value to reduce interference to other devices.

[0036] refer to Figure 4 In step S13, the specific steps are as follows: S131: Based on the detection of the communication method of the audio equipment, multiple sub-communication items are determined, and the communication content of each sub-communication item is marked. Based on the identification of the communication content of each sub-communication item, multiple communication features are determined. Based on each sub-communication item and the corresponding multiple communication features, the communication effect coefficient of each sub-communication item is determined. S132: Collect the current working task of the audio equipment, and determine the first level of communication control content based on the current working task of the audio equipment and the communication content of each sub-communication item; S133: Determine the second level of communication control content based on the current working task of the audio equipment and the communication effect coefficients of each sub-communication item, and determine the communication control system of the audio equipment based on the training of the first level of communication control content and the second level of communication control content.

[0037] In the embodiments of this application, multiple sub-communication items are determined based on the detection of the communication method of the audio device, and the communication content of each sub-communication item is marked. Multiple communication features are determined based on the identification of the communication content of each sub-communication item. The communication effect coefficient of each sub-communication item is determined based on each sub-communication item and the corresponding multiple communication features. This approach takes into account the overall consideration of each sub-communication item and the corresponding multiple communication features, ensuring the accuracy of the communication effect coefficient of each sub-communication item.

[0038] At this point, the system identifies all ongoing communication sessions by analyzing currently active protocol stack instances and data streams. Each session is a "sub-communication project." Subsequently, the system tagged each project with a content type (such as A2DP audio, BLE control, etc.) by parsing the metadata of the protocol header and data payload. This forms the basis for subsequent differentiated processing.

[0039] For each tagged communication item, a deep analysis is performed to extract its quantitative and comparable physical and business characteristics. These characteristics constitute the item's "technical profile," including: traffic characteristics (such as throughput and burstiness), quality of service characteristics (such as maximum tolerable latency and jitter), and protocol and behavioral characteristics (such as encoding / decoding formats and retransmission mechanisms).

[0040] Multi-dimensional technical features are mapped to a single, unified scalar value for cross-project comparison and prioritization. The system has a built-in multi-attribute decision analysis model (usually a weighted summation function) that substitutes the feature values ​​of each project into the calculation. The weights of different features are dynamic and related to the current user task. Finally, a normalized coefficient (e.g., between 0 and 1) is calculated. The higher the coefficient, the greater the contribution of the project to the overall user experience in the current context, or the more severe the negative impact of its failure.

[0041] Specifically, the system detected three active communication sessions and identified them as three sub-communication items: Item P1: Connection with the mobile phone; by analyzing the L2CAP channel, its communication content is marked as "A2DP stereo audio stream"; Item P2: Connection with the wireless subwoofer; according to the proprietary protocol, its communication content is marked as "proprietary 2.4G subwoofer audio stream"; Item P3: Connection with the mobile app; through BLEUID, its communication content is marked as "BLE control and OTA signaling".

[0042] Project P1 (A2DP audio): VBR, average bitrate 320kbps, maximum tolerable latency 150ms, using AAC encoding; Project P2 (proprietary 2.4G subwoofer): CBR, bitrate 600kbps, maximum tolerable latency 20ms, transmitting uncompressed PCM audio; Project P3 (BLE control): extremely low bandwidth, intermittent bursts, insensitive to latency, requiring high reliability.

[0043] The system assumes the current user task is "immersive music enjoyment," therefore, "latency" and "jitter" in the QoS features are given the highest weight. The P1 coefficient is calculated as follows: P1 has relatively lenient latency and jitter requirements; although it is the primary sound source, its buffering mechanism can tolerate some fluctuations. After evaluation, its communication performance coefficient is determined to be 0.7. The P2 coefficient is calculated as follows: P2 has extremely stringent latency and jitter requirements; its performance directly determines the bass synchronization effect, which is key to "immersion." Any lag will be easily perceived by the user; therefore, its communication performance coefficient is rated as the highest, at 0.9. The P3 coefficient is calculated as follows: P3 is used for volume adjustment or EQ settings; a half-second delay in response is almost imperceptible to the user, and its failure does not affect the core music playback function; therefore, its communication performance coefficient is the lowest, at 0.1.

[0044] Furthermore, the current working task of the audio equipment is collected, and the first level of communication control content is determined based on the current working task of the audio equipment and the communication content of each sub-communication item. This takes into account the overall consideration of the current working task of the audio equipment and the communication content of each sub-communication item, ensuring the accuracy of the first level of communication control content.

[0045] At this point, the system identifies the current core task by listening to events in the application framework, parsing the user interface (UI) state machine, or reading the system-level task queue. These tasks can originate from direct user operations, preset automated scenarios, or maintenance tasks triggered by the system background. The system will abstract specific user behaviors into standardized task labels (such as TASK_AUDIO_PLAYBACK), enabling the underlying communication system to understand user intent without needing to concern itself with the specific interaction method.

[0046] The system associates the user's macro-level intent (task) with the specific communication activities (projects) being executed by the system, thereby defining the core objectives and qualitative constraints of communication control. The system maintains a mapping table or rule base to define the core communication items that each task depends on. Based on this mapping, the system generates "first-level communication control content," which is a set of qualitative, high-level policy statements that define "what must be guaranteed" and "to what extent."

[0047] Specifically, based on the three sub-communication items identified by S131 (P1: A2DP audio stream, P2: private 2.4G subwoofer stream, P3: BLE control signaling), the user clicks the "Cinema Mode" button through the mobile app to start playing a movie that supports Dolby Atmos; the application layer of the audio device receives this event and abstracts it into a composite current task: TASK_IMMERSIVE_CINEMA_EXPERIENCE (immersive cinema experience). This task not only includes audio playback, but also implies extremely high requirements for sound field synchronization, bass effects, and surround sound.

[0048] The system queries the rule base and finds that TASK_IMMERSIVE_CINEMA_EXPERIENCE strongly depends on P1 (main channel audio) and P2 (subwoofer audio), while its dependence on P3 (App control) is very low. Based on this mapping, the system generates the following first-level communication control content (represented in the form of policy rules): Core business assurance strategy: {POLICY_CORE_BUSINESS:[P1,P2]}; explicitly states that P1 and P2 are the core of this task, and the continuity and quality of their communication are of the highest priority; Service quality bottom line strategy: {POLICY_QOS_FLOOR:{P1:{MAX_DELAY:"100ms",MAX_JITTER:"30ms"},P2:{MAX_DELAY:"15ms",MAX_JITTER:"5ms"}}}; sets an uncompromising performance baseline for the two core projects; especially P2 (subwoofer), whose latency and jitter requirements are extremely stringent, which are crucial to ensuring audio-visual synchronization and bass impact; Non-core business degradation strategy: {POLICY_NON_CORE_DEGRADATION:[P3]}; allows for delayed processing or degradation of P3 (such as the volume adjustment command of an app) when core resources are scarce, in order to protect core businesses; Collaborative work strategies: {POLICY_COLLABORATION:{P1,P2:"SYNCHRONIZED_PLAYBACK"}}; This requires that P1 and P2 maintain precise time synchronization, and any desynchronization is considered a serious fault.

[0049] Therefore, the second level of communication control content is determined based on the current working task of the audio equipment and the communication effect coefficients of each sub-communication item. The communication control system of the audio equipment is determined based on the training of the first and second level of communication control content. This approach takes into account the overall consideration of the training of the first and second level of communication control content, ensuring the accuracy of the communication control system of the audio equipment. At the same time, the communication scenario of the audio equipment is introduced, and the communication method of the audio equipment is further controlled. This approach takes into account the overall consideration of the communication content of each sub-communication item, the corresponding communication effect coefficients, and the current working task of the audio equipment, thereby improving the accuracy of the communication control system of the audio equipment.

[0050] At this point, the quantified project value (effect coefficient) in S131 is combined with the strategic intent (current task) in S132 to generate a refined and quantifiable resource allocation scheme. The system dynamically adjusts the weight of each "communication effect coefficient" according to the "current work task". Using the adjusted weights, the system uses an optimization algorithm to calculate the specific allocation ratio of limited system resources (CPU time, DMA bandwidth, scheduling priority, etc.) among the various sub-communication projects. The output "secondary communication control content" is a set of specific and operable configuration parameters.

[0051] The first and second layers are integrated, verified, and conflict resolved. Here, "training" is a logical synthesis and verification process. The system inputs the two layers of control content into a policy synthesis engine to check whether the resource allocation scheme of the second layer meets all the policy bottom lines set by the first layer. When inconsistencies or resource conflicts occur, the engine will make a decision based on preset meta-rules (such as "core business takes precedence over auxiliary business"). After verification and resolution, the engine outputs the final "communication control system"—a complete and self-consistent set of configurations, which will be immediately sent to the underlying hardware and firmware for execution.

[0052] Specifically, S131 results: P1 (A2DP) effect coefficient 0.7, P2 (private 2.4G) effect coefficient 0.9, P3 (BLE) effect coefficient 0.1; S132 results: the current task is TASK_IMMERSIVE_CINEMA_EXPERIENCE, the first level of control requires P1 and P2 to be synchronized and have extremely low latency (P2 < 15ms). Because the task is an "immersive cinematic experience," the system significantly increases the weight of "latency" and "synchronization" in the effect coefficient calculation, further highlighting the relative importance of P2 (coefficient 0.9, ultra-low latency). Based on the adjusted weights, the system allocates the shared CPU / DSP resources of the ATS2835P chip as follows: P2 (private 2.4G): 70% of real-time processing resources; P1 (A2DP): 25% of processing resources; P3 (BLE): 5% of processing resources. The second layer of control is specifically defined as follows: {SCHEDULER_CONFIG:{P2:PRIORITY_REALTIME_CRITICAL,TIME_SLICE:"70%"},{P1:PRIORITY_HIGH,TIME_SLICE:"25%"},{P3:PRIORITY_LOW,TIME_SLICE:"5%"}}.

[0053] The strategy synthesis engine begins operation, receiving the first level (P1 / P2 latency <15ms, synchronization is required) and the second level (P2 occupies 70% of resources, P1 occupies 25%) as input. Through system modeling, the engine determines that allocating 70% of the CPU to P2 is sufficient to ensure its latency is far below 15ms; simultaneously, allocating 25% to P1 also meets its 100ms latency requirement. Conclusion: The second level solution meets the first level's minimum requirements, and consistency is achieved; there are no major conflicts; the resource allocation ratio of P2 and P1 is consistent with their effectiveness coefficients and task importance.

[0054] The engine outputs the final "communication control system" and immediately deploys it onto the ATS2835P chip: Hybrid protocol stack scheduler: reconfigured, P2 tasks are given the highest real-time priority and preemptively executed to ensure minimal processing latency; P1 tasks are high priority and run when P2 is idle; Dual-mode cooperative anti-interference algorithm: activated, giving P2 control over channel selection to ensure it operates at the optimal frequency; Hardware acceleration module: the system enables a dedicated hardware acceleration engine for the P2 data stream to further reduce CPU load and latency; Power management: due to the current high-performance task, the system disables power-saving modes for all non-core modules to ensure the RF and processor operate at peak performance.

[0055] refer to Figure 5 In step S14, the specific steps are as follows: S141: Real-time monitoring of the communication control system, collecting multiple communication data from the audio equipment, obtaining the response information of the audio equipment, determining the first communication lag content based on the multiple communication data of the audio equipment and the communication control system, determining the second communication lag content based on the response information of the audio equipment and the communication control system, and determining the communication lag event of the audio equipment based on the first communication lag content and the second communication lag content. S142: Match multiple sub-communication modules, determine the communication priority of multiple sub-communication modules based on the matching of multiple sub-communication modules, collect the communication status of multiple sub-communication modules, and determine the first communication optimization measure based on the communication priority of multiple sub-communication modules and the communication lag event of the audio equipment. S143: Determine a second communication optimization measure based on the communication status of multiple sub-communication modules and the communication lag event of the audio equipment, and determine a communication optimization event based on the first and second communication optimization measures.

[0056] In the embodiments of this application, a real-time monitoring communication control system is used to collect multiple communication data from the audio equipment and obtain the response information of the audio equipment. Based on the multiple communication data of the audio equipment and the communication control system, a first communication lag content is determined. Based on the response information of the audio equipment and the communication control system, a second communication lag content is determined. Based on the first and second communication lag contents, a communication lag event of the audio equipment is determined. This system takes into account both the first and second communication lag contents as a whole, ensuring the accuracy of the communication lag event of the audio equipment.

[0057] At this time, the system continuously collects runtime data from the monitoring points of each sub-communication module identified in S11. This data constitutes "multiple communication data", including real-time throughput, latency, jitter, packet loss rate (PER), received signal strength indication (RSSI), etc. At the same time, the system obtains "response information" from the audio processing unit or application layer, such as the buffer level of the audio decoder or the connection status reported by the user interface. This information reflects the actual impact of communication performance on upper-layer services.

[0058] The system compares the collected raw data with the preset expected value (from the communication control system) to identify specific performance deviations. It then compares the collected "communication data" with the QoS thresholds set in the "communication control system" to generate a "first communication lag content" based on objective data. Next, the system compares the "response information" with the expected behavior to generate a "second communication lag content" based on business impact. Finally, the system merges and correlates these two lag contents to generate a high-level, semantic "communication lag event," which not only describes the problem but also includes context and causes.

[0059] Specifically, the audio equipment is performing an "immersive cinema experience" task, and the S13 has established a strict communication control system for it; the system is continuously collecting data at a frequency of 100 times per second; suddenly, it detects an anomaly in the private 2.4G link (P2) with the wireless subwoofer: end-to-end latency: soared from a stable 12ms to 35ms; packet loss rate (PER): increased from 0.1% to 5%; RSSI: dropped sharply from -70dBm to -90dBm; at the same time, the audio DSP reports an emergency event to the main control CPU: EVENT_AUDIO_BUFFER_LOW, which specifically points to the PCM buffer of the subwoofer channel, whose level has fallen below 20% and is about to overflow, which will cause the user to hear obvious bass stuttering or interruption.

[0060] The first communication lag is identified: The system's diagnostic module compares the real-time data with the communication control system set in S13; the control system requires P2 delay <15ms and PER <1%; the current data significantly exceeds these limits; therefore, the system generates the first lag content: Content 1: {TYPE:"QOS_VIOLATION",SOURCE:"P2",METRIC:"LATENCY",VALUE:35ms,LIMIT:15ms}; Content 2: {TYPE:"QOS_VIOLATION",SOURCE:"P2",METRIC:"PER",VALUE:5%,LIMIT:1%}.

[0061] Determining the second communication lag: The diagnostic module analyzes the response information from the audio DSP; EVENT_AUDIO_BUFFER_LOW is a high-severity service-impacting event; therefore, the system generates the second lag content: Content 3: {TYPE:"BUSINESS_IMPACT",SOURCE:"P2",SYMPTOM:"AUDIO_BUFFER_UNDERRUN_IMMINENT",SEVERITY:"CRITICAL"}.

[0062] The event correlation engine merges these three independent delayed events; it finds that objective QoS degradation (events 1 and 2) and subjective business impact (event 3) occur simultaneously, both pointing to the same item P2; the sharp drop in RSSI provides a strong clue as to the cause; the system generates a high-level communication delay event: Final Event: {EVENT_ID:"EVT_2024_1027_001",EVENT_NAME:"CRITICAL_SUBWOOFER_LINK_DEGRADATION",AFFECTED_PROJECT:"P2",TRIGGERS:["QOS_VIOLATION","BUSINESS_IMPAC T"],OBSERVED_DATA:{LATENCY:"35ms",PER:"5%",RSSI:"-90dBm"},HYPOTHESIZED_ROOT_CAUSE:"SuddenandsevereRFinterferenceorobstructiononthe2.4Glink."}.

[0063] Furthermore, multiple sub-communication modules are matched, and their communication priorities are determined based on this matching. The communication status of these sub-communication modules is also collected. Based on the communication priorities of the sub-communication modules and the communication lag events of the audio equipment, a first communication optimization measure is determined. This approach takes into account both the communication priorities of the sub-communication modules and the communication lag events of the audio equipment, ensuring the accuracy of the first communication optimization measure.

[0064] At this point, the system matches the sub-communication items affected by the "communication lag event" identified in S141 with the complete item list, and rereads the "communication effect coefficient" and the predetermined "scheduling priority" of these affected items and related items. At the same time, the system immediately performs a snapshot-style status collection on all relevant sub-communication modules to obtain their latest RSSI, PER, buffer level, etc. This process ensures that subsequent emergency decisions are based on the latest and most accurate information.

[0065] The decision engine, based on the severity of the delayed event and the priority of the affected projects, follows the principle that when a high-priority project lags, the system has the right to "requisition" resources from low-priority projects. These "first communication optimization measures" are usually resource reallocations or aggressive parameter adjustments that take effect immediately and have a wide impact. Specifically, they include: resource preemption (such as increasing the CPU quota of delayed projects and suspending low-priority tasks), aggressive parameter adjustments (such as increasing the transmit power to the maximum and switching to the most robust modulation scheme), and task degrading or suspension.

[0066] Specifically, after an event (pointing to P2: private 2.4G subwoofer stream) is generated in S141, the system matches the delayed event with the project list and confirms that the core project affected is P2. According to the "immersive cinema experience" task control system set in S133, the priority of each project is: P2 (highest real-time priority) > P1 (high priority) > P3 (normal priority).

[0067] The system immediately takes a snapshot: P2: RSSI -90dBm, PER 5%, critical condition; P1 (A2DP): RSSI -78dBm, PER 0.5%, good condition but slightly interfered; P3 (BLE): RSSI -82dBm, PER 0.1%, stable condition. The decision engine identified a critical-level lag in the highest-priority P2 link; based on the "preserve high priority" principle, the most aggressive measures must be taken immediately to restore the link quality of P2; the system formulated a series of rapid response measures, forming a combined approach: Measure 1 (Resource Preemption): The system will immediately suspend the task scheduling of P3 and allocate all the resources it occupies to P2; Measure 2 (Aggressive Parameter Adjustment): The system will push the transmit power of P2 to the limit of the ATS2835P chip and sacrifice the data rate for anti-interference capability; Measure 3 (Task Degradation): In order to create a better environment for P2, the system will also slightly downgrade the second highest priority P1.

[0068] Therefore, the second communication optimization measure is determined based on the communication status of multiple sub-communication modules and the communication lag event of the audio equipment. The communication optimization event is determined based on the first and second communication optimization measures, which is compatible with the overall consideration of the first and second communication optimization measures and ensures the accuracy of the communication optimization event.

[0069] At this point, the supplement and deepening of the "rapid response" measures in S142 differs from S142's reliance on priority. This step focuses more on analyzing the latest "communication status" to find the root cause of the problem and developing more targeted solutions. These "secondary communication optimization measures" are usually more intelligent and adaptable, specifically including: intelligent channel switching (planning and executing a complete switching process to a cleaner channel), collaborative avoidance (leveraging the advantages of a single-chip solution, with unified decision-making by a central coordinator to achieve overall optimal avoidance at the system level), and path / mode switching (activating a backup solution when the primary link cannot be restored).

[0070] The system integrates the optimization measures S142 (first level) and S143 (second level) to form a comprehensive, multi-layered action plan, taking into account the temporal dependencies of the measures. This integrated plan is encapsulated into a structured "communication optimization event," which includes all the action sequences to be executed, target modules, expected effects, and execution schedules. This event is submitted to the system's execution engine, which will sequentially call the corresponding drivers and APIs to complete the dynamic reconfiguration of the system, thereby achieving automatic repair of communication lag events.

[0071] Specifically, after S142 had already implemented the first optimization measure (pausing P3, maximizing P2 power, etc.), temporarily stabilizing the situation, but the link quality of P2 (RSSI-90dBm) was still very poor, the system performed a snapshot status acquisition again after implementing the first measure. It found that P2's RSSI was still extremely low, but the spectrum scan showed that there was an extremely strong and stable narrowband interference source near its current operating channel 10.

[0072] The system decides to adopt a smarter strategy: Measure 1 (Intelligent Channel Switching): {ACTION:"INTELLIGENT_CHANNEL_SWITCH",TARGET:"P2",DETAILS:"Planafasthop to clean channel 11.Coordinate with the subwoofer receiver to synchronize the switch with the next 20ms."} The system plans a precise channel switching action; Measure 2 (Cooperative Avoidance): {ACTION:"COLLABORATIVE_AVOIDANCE",TARGET:"P1&P2",DETAILS:"Activate the co-existence algorithm.Instruct the Bluetooth stack (P1) to modify its Adaptive Frequency Hopping (AFH) map topically exclude channel 11 and its adjacent channels."} The system activates the core co-existence algorithm, causing P1 to actively yield to P2, ensuring that P2 is no longer interfered with by itself after switching to the new channel.

[0073] The system's strategy integration engine integrates the measures of S142 and S143 and schedules their execution order: Execute immediately: S142's resource preemption and power maximization (already executed); Execute within 10ms: S143's cooperative avoidance instruction, notifying P1 to modify the frequency hopping map; Execute within 20ms: S143's intelligent channel switching, after P1 yields, P2 safely hops to channel 11; Continuous monitoring: After the switch is completed, continuously monitor P2's RSSI and PER, and if they return to normal, gradually resume P3's tasks after 100ms.

[0074] Generate the final event: This complete action plan is encapsulated into a communication optimization event: {EVENT_ID:"OPT_RESTORE_SUBWOOFER_LINK",ACTIONS:[{ACTION:"MAINTAIN_HIGH_POWER",TARGET:"P2"},{ACTION:"EXECUTE_AVOIDANCE",TARGET:"P1"},{ACTION:"EXECUTE_CHANNEL_SWITCH",TARGET:"P2"},{ACTION:"MONITOR_AND_RECOVER"}],TIMEOUT:"500ms"}.

[0075] refer to Figure 6 In step S15, the specific steps are as follows: S151: Based on the detection of communication optimization events, multiple sub-communication optimization measures are determined. Among the multiple sub-communication optimization measures, the corresponding sub-communication optimization content is determined based on the identification of the sub-communication optimization measures. At the same time, the working status of the audio equipment is collected, and the first dynamic communication coefficient is determined based on the working status of the audio equipment and the multiple sub-communication optimization contents. S152: Determine the second dynamic communication coefficient based on the communication control system and multiple sub-communication optimization contents, and determine the dynamic communication mode of the audio equipment according to the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication mode. S153: Monitor the audio equipment in real time and collect the load of the audio equipment. Determine the first dynamic communication content based on the dynamic communication mode and the load of the audio equipment. Determine the second dynamic communication content based on the dynamic communication mode and the communication scenario of the audio equipment. Determine the dynamic communication event of the audio equipment based on the first dynamic communication content and the second dynamic communication content.

[0076] In the embodiments of this application, multiple sub-communication optimization measures are determined based on the detection of communication optimization events. Among the multiple sub-communication optimization measures, the corresponding sub-communication optimization content is determined based on the identification of the sub-communication optimization measures. At the same time, the working status of the audio device is collected, and a first dynamic communication coefficient is determined based on the working status of the audio device and the multiple sub-communication optimization contents. This approach takes into account both the working status of the audio device and the overall consideration of the multiple sub-communication optimization contents, ensuring the accuracy of the first dynamic communication coefficient.

[0077] At this point, the system deconstructs and abstracts the specific "communication optimization events" that have been executed, with the aim of extracting reusable general strategy knowledge from a one-time successful response. The system parses the specific atomic instructions in the event (such as SET_TX_POWER(+10dBm)), identifies them as "sub-communication optimization measures", and classifies them into higher-level "sub-communication optimization content" (such as "aggressive power boost") through pattern matching. This process is the induction from specific operations to general strategies, which is the foundation for the system's learning and adaptation.

[0078] The system collects indicators reflecting the physical status of the device in real time through internal sensors and management units, such as battery level, chip temperature, and CPU load. The system correlates the working status with each optimization content for evaluation and generates a quantified cost / risk coefficient. This coefficient is an adjustment factor. For example, the coefficient for "aggressive power increase" is 0.9 when the battery is sufficient (encouraging implementation), but rises to 1.3 when the battery is low or the temperature is high (strongly discouraged), thus providing a cost basis for decision-making.

[0079] Furthermore, based on the communication control system and multiple sub-communication optimization contents, the second dynamic communication coefficient is determined. The dynamic communication mode of the audio equipment is determined according to the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication mode. This takes into account the overall consideration of the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication mode, and ensures the accuracy of the dynamic communication mode of the audio equipment.

[0080] At this point, the system compares the "sub-communication optimization content" extracted in S151 with the core objectives (such as "ultimate performance", "balanced mode" or "ultra-long battery life") represented by the "communication control system" established in S13. This consistency in strategy is quantified as the "second dynamic communication coefficient", which reflects the "strategic value" of the optimization content rather than the "physical cost". For example, the coefficient of "aggressive power enhancement" is 1.2 under the "ultimate performance" objective, but it is 0.7 under the "ultra-long battery life" objective.

[0081] The system calculates a "comprehensive score" for each key sub-communication optimization content. This score integrates multiple dimensions of consideration, and the formula is usually: Comprehensive score = Original communication effect coefficient (S131) ​​× First dynamic communication coefficient (S151) × Second dynamic communication coefficient (S152). This score balances "ease of use" (effect coefficient), "affordability" (first coefficient), and "whether it should be used" (second coefficient). Subsequently, based on the calculated comprehensive score, the system queries the internally maintained "Comprehensive score > Dynamic communication mode" mapping table to determine the macro-behavioral mode that the device should enter, such as "performance aggressive mode", "balanced mode", or "energy saving mode".

[0082] Therefore, by monitoring the audio equipment in real time and collecting its load data, the system determines the first dynamic communication content based on the dynamic communication mode and the equipment's load, and the second dynamic communication content based on the same dynamic communication mode and the equipment's communication scenario. Based on these two dynamic communication contents, the system determines the dynamic communication events of the audio equipment. This approach considers both the first and second dynamic communication contents holistically, ensuring the accuracy of the audio equipment's dynamic communication events. Furthermore, by introducing communication optimization events, the system further manages the dynamic communication mode, achieving a holistic consideration of the dynamic communication mode, the audio equipment's load, and the corresponding communication scenario, thus improving the accuracy of the audio equipment's dynamic communication mode.

[0083] At this time, the system continuously monitors the system's internal load indicators (such as CPU / DSP utilization, memory usage, buffer level, etc.) at a high frequency; it interprets and responds to these load changes according to the currently active "dynamic communication mode"; for example, in "performance aggressive mode", 75% CPU load is considered "normal", and the system will decide to maintain or increase the CPU frequency; while in "energy saving mode", the same load is considered "overload", and the system will immediately trigger a frequency reduction strategy. The result of this interpretation process is the "first dynamic communication content".

[0084] The system cross-analyzes the "dynamic communication mode" with the "communication scenario" identified in S121 to generate adaptive strategies for the external environment. For example, in the "balanced mode", if the scenario is a "quiet living room", the system will reduce the transmission power to save energy; if the scenario is a "high-interference outdoor", it will activate active anti-interference measures to prioritize link reliability. This result is the "second dynamic communication content". The system merges the first and second dynamic communication contents to generate a final, real-time, and executable "dynamic communication event" and immediately sends it out for execution, thereby completing the entire intelligent closed loop.

[0085] Please see Figure 7 , Figure 7 This is a schematic diagram of the structural composition of the communication control system of the audio equipment in an embodiment of the present invention; the communication control system of the audio equipment includes: The identification module 21 is used to determine the database of audio devices based on the detection of audio devices, determine the corresponding communication space based on the traversal of the database of audio devices, and determine multiple sub-communication modules based on the identification of the communication space. The communication mode module 22 is used to determine the communication scenario of the audio device based on multiple environmental data of the audio device and the current location of the audio device, and to determine the communication mode of the audio device according to the communication scenario of the audio device and the communication status of multiple sub-communication modules. The communication control system module 23 is used to determine multiple sub-communication items based on the detection of the communication method of the audio equipment, and to determine the communication control system of the audio equipment according to the communication content of each sub-communication item, the corresponding communication effect coefficient and the current working task of the audio equipment. The communication optimization event module 24 is used to determine the communication lag event of the audio device based on multiple communication data of the audio device, the response information of the audio device and the communication control system in the communication control system, and to determine the communication optimization event based on the communication lag event, the communication priority of multiple sub-communication modules and the corresponding communication status. The dynamic communication event module 25 is used to determine multiple sub-communication optimization contents based on the identification of communication optimization events, determine the dynamic communication mode of the audio equipment based on the working status of the audio equipment, the communication control system and multiple sub-communication optimization contents, and determine the dynamic communication events of the audio equipment based on the dynamic communication mode, the load of the audio equipment and the corresponding communication scenario.

[0086] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A communication control method for an audio device, characterized in that, include: The database of audio equipment is determined based on the detection of audio equipment, the corresponding communication space is determined by traversing the database of audio equipment, and multiple sub-communication modules are determined based on the identification of the communication space. The communication scenario of the audio equipment is determined based on multiple environmental data and the current location of the audio equipment. The communication method of the audio equipment is determined based on the communication scenario and the communication status of multiple sub-communication modules. Based on the detection of the communication method of the audio equipment, multiple sub-communication items are determined. The communication control system of the audio equipment is determined according to the communication content of each sub-communication item, the corresponding communication effect coefficient, and the current working task of the audio equipment. In the communication control system, the communication lag event of the audio equipment is determined based on multiple communication data of the audio equipment, the response information of the audio equipment, and the communication control system. The communication optimization event is determined based on the communication lag event, the communication priority of multiple sub-communication modules, and the corresponding communication status. Based on the identification of communication optimization events, multiple sub-communication optimization contents are determined. Based on the working status of the audio equipment, the communication control system, and the multiple sub-communication optimization contents, the dynamic communication mode of the audio equipment is determined. Based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, the dynamic communication events of the audio equipment are determined.

2. The communication control method for audio equipment according to claim 1, characterized in that, The database of audio devices is determined based on the detection of audio devices. A corresponding communication space is determined by traversing this database. Multiple sub-communication modules are determined based on the identification of this communication space, including: The control chip of the audio equipment is marked based on the detection of the audio equipment. The database of the audio equipment is determined by tracing the control chip. The database of the audio equipment is then traversed. At this time, multiple spatial nodes are determined by traversing the database of the audio equipment. The corresponding communication space is determined by tracing the source of each spatial node. The transmission path of communication data is determined based on the identification of the communication space, multiple communication nodes are determined based on the detection of the transmission path, and corresponding sub-communication modules are matched based on the tracing of each communication node, so as to collect multiple sub-communication modules.

3. The communication control method for audio equipment according to claim 1, characterized in that, The communication scenario of the audio device is determined based on multiple environmental data and its current location. The communication method of the audio device is then determined based on this scenario and the communication status of multiple sub-communication modules, including: The system collects the current location of the audio equipment, determines multiple environmental data based on the environmental detection of the current location of the audio equipment, and determines the communication scenario of the audio equipment based on the multiple environmental data, the current location, and the overall shape of the audio equipment. The corresponding communication status is determined based on the detection of multiple sub-communication modules. The communication status of multiple sub-communication modules is collected, and the communication mode of the audio equipment is determined according to the communication scenario of the audio equipment, the communication status of multiple sub-communication modules, and the current working task of the audio equipment.

4. The communication control method for audio equipment according to claim 1, characterized in that, The method of detecting the communication mode of the audio equipment determines multiple sub-communication items. Based on the communication content of each sub-communication item, the corresponding communication effect coefficient, and the current working task of the audio equipment, a communication control system for the audio equipment is determined, including: Multiple sub-communication items are determined based on the detection of the communication method of the audio equipment, and the communication content of each sub-communication item is marked. Multiple communication features are determined based on the identification of the communication content of each sub-communication item, and the communication effect coefficient of each sub-communication item is determined based on each sub-communication item and the corresponding multiple communication features.

5. The communication control method for audio equipment according to claim 4, characterized in that, The method of determining multiple sub-communication items based on the detection of the communication method of the audio equipment, and determining the communication control system of the audio equipment based on the communication content of each sub-communication item, the corresponding communication effect coefficient, and the current working task of the audio equipment, also includes: Collect the current working task of the audio equipment, and determine the first level of communication control content based on the current working task of the audio equipment and the communication content of each sub-communication item; The second level of communication control content is determined based on the current working task of the audio equipment and the communication effect coefficients of each sub-communication item. The communication control system of the audio equipment is determined based on the training of the first level of communication control content and the second level of communication control content.

6. The communication control method for audio equipment according to claim 1, characterized in that, In the communication control system, a communication lag event of the audio equipment is determined based on multiple communication data from the audio equipment, the response information of the audio equipment, and the communication control system. A communication optimization event is then determined based on this lag event, the communication priorities of multiple sub-communication modules, and the corresponding communication status, including: The system monitors the communication control system in real time, collects multiple communication data from the audio equipment, and obtains the response information from the audio equipment. Based on the multiple communication data from the audio equipment and the communication control system, it determines the first communication lag content, determines the second communication lag content based on the response information from the audio equipment and the communication control system, and determines the communication lag event of the audio equipment based on the first and second communication lag contents.

7. The communication control method for audio equipment according to claim 6, characterized in that, In the communication control system, the communication lag event of the audio equipment is determined based on multiple communication data from the audio equipment, the response information of the audio equipment, and the communication control system. A communication optimization event is then determined based on this communication lag event, the communication priorities of multiple sub-communication modules, and the corresponding communication status. The system also includes: Multiple sub-communication modules are matched, and the communication priority of the multiple sub-communication modules is determined based on the matching of the multiple sub-communication modules. The communication status of the multiple sub-communication modules is collected, and the first communication optimization measure is determined according to the communication priority of the multiple sub-communication modules and the communication lag event of the audio equipment. The second communication optimization measure is determined based on the communication status of multiple sub-communication modules and the communication lag event of the audio equipment, and the communication optimization event is determined based on the first and second communication optimization measures.

8. The communication control method for audio equipment according to claim 1, characterized in that, The process involves identifying multiple sub-communication optimization contents based on the recognition of communication optimization events, determining the dynamic communication mode of the audio equipment based on its operating state, communication control system, and multiple sub-communication optimization contents, and determining the dynamic communication events of the audio equipment based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, including: Multiple sub-communication optimization measures are determined based on the detection of communication optimization events. Among the multiple sub-communication optimization measures, the corresponding sub-communication optimization content is determined based on the identification of the sub-communication optimization measures. At the same time, the working status of the audio equipment is collected, and the first dynamic communication coefficient is determined based on the working status of the audio equipment and the multiple sub-communication optimization contents. The second dynamic communication coefficient is determined based on the communication control system and multiple sub-communication optimization contents. The dynamic communication mode of the audio equipment is determined according to the mapping relationship between the first dynamic communication coefficient, the second dynamic communication coefficient and the dynamic communication mode.

9. The communication control method for an audio device according to claim 8, characterized in that, The process of determining multiple sub-communication optimization contents based on the identification of communication optimization events, determining the dynamic communication mode of the audio equipment based on the operating state of the audio equipment, the communication control system, and the multiple sub-communication optimization contents, and determining the dynamic communication events of the audio equipment based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, further includes: The system monitors audio equipment in real time and collects the load of the audio equipment. Based on the dynamic communication mode and the load of the audio equipment, it determines the first dynamic communication content, determines the second dynamic communication content based on the dynamic communication mode and the communication scenario of the audio equipment, and determines the dynamic communication event of the audio equipment based on the first dynamic communication content and the second dynamic communication content.

10. A communication control system for an audio device, characterized in that, The communication control system of the audio equipment is applied to the communication control method of the audio equipment as described in any one of claims 1-9, and the communication control system of the audio equipment includes: The identification module is used to determine the database of audio devices based on the detection of audio devices, determine the corresponding communication space based on the traversal of the audio device database, and determine multiple sub-communication modules based on the identification of the communication space. The communication mode module is used to determine the communication scenario of the audio equipment based on multiple environmental data of the audio equipment and the current location of the audio equipment, and to determine the communication mode of the audio equipment according to the communication scenario of the audio equipment and the communication status of multiple sub-communication modules. The communication control system module is used to determine multiple sub-communication items based on the detection of the communication method of the audio equipment, and to determine the communication control system of the audio equipment according to the communication content of each sub-communication item, the corresponding communication effect coefficient and the current working task of the audio equipment. The communication optimization event module is used in the communication control system to determine the communication lag event of the audio equipment based on multiple communication data of the audio equipment, the response information of the audio equipment, and the communication control system. Based on the communication lag event, the communication priority of multiple sub-communication modules, and the corresponding communication status, the communication optimization event is determined. The dynamic communication event module is used to determine multiple sub-communication optimization contents based on the identification of communication optimization events. Based on the working status of the audio equipment, the communication control system, and the multiple sub-communication optimization contents, the dynamic communication mode of the audio equipment is determined. Based on the dynamic communication mode, the load of the audio equipment, and the corresponding communication scenario, the dynamic communication events of the audio equipment are determined.

Images