Wireless loudspeaker box group cooperative control method and system based on external Bluetooth transmitting and receiving array

Abstract

The invention discloses a wireless loudspeaker box group cooperative control method and system based on an external Bluetooth transmitting and receiving array, and relates to the technical field of wireless audio control. UWB high-precision positioning and Bluetooth RSSI fingerprint data are fused, an error correction model is constructed, environmental interference data are acquired in real time in combination with spectrum scanning, and the problems of single-technology positioning drift and signal crosstalk are solved. And adopting an improved K-means clustering algorithm, dynamically and adaptively partitioning the sound field according to the movement speed and density of the user, and optimizing the physical topology path of the Bluetooth array based on the interference intensity. A user density change rate, a cluster offset distance and an interference intensity threshold are set, sound field reconstruction is triggered in real time, and partition lag of a traditional scheme is avoided. The Bluetooth array is controlled to switch narrow beam directional transmission, and a multi-user priority arbitration model is combined, so that the concurrent bearing capacity of the system is improved. A wireless sound box group cooperative control scheme integrating dynamic sound field adaptation, high-concurrency instruction scheduling, anti-interference transmission and cross-brand compatibility is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless audio control, and specifically to a method and system for collaborative control of a wireless speaker group based on an external Bluetooth transmitting and receiving array. Background Art

[0002] Traditional wireless speaker group control technologies mainly rely on star topology connections of Bluetooth or Wi-Fi, where a single master device distributes audio streams and coordinates slave device synchronization. However, in dynamic and changing practical application scenarios (such as commercial performances, large-scale exhibitions), such solutions expose a series of significant defects. The prior art cannot achieve dynamic adaptation of sound field zoning. Traditional methods usually adopt preset fixed sound field modes (such as left / right channel zoning), and their zoning rules depend on the physical installation positions of the speakers rather than the real-time user distribution. When the user group moves or the population density in a local area changes suddenly, it is extremely easy to cause sound field coverage imbalance - in high-density areas, the information transmission fails due to insufficient volume, while in low-density areas, auditory interference is caused by redundant superposition of sound waves. For example, at a concert scene, when the audience gathers towards the front of the stage, the traditional solution still plays according to the initial uniform distribution, resulting in overloaded sound in the front row and blurred listening experience in the back row. Secondly, the system stability in high-concurrency control scenarios is seriously insufficient. When multiple users simultaneously send commands such as sound field switching and volume adjustment through a mobile phone APP, the traditional Bluetooth solution is limited by the single-path communication between the master and slave devices, and the command queue backlog causes response delays (generally exceeding 500 ms), and even command loss due to channel congestion. This problem is particularly prominent in exhibitions with tens of thousands of people. When exhibitors frequently adjust the explanation volume in different exhibition areas, the system frequently freezes or crashes.

[0003] In addition, multi-region signal interference and cross-brand compatibility defects further restrict the technical practicability. Existing solutions mostly adopt an omnidirectional broadcast mode, and the Bluetooth signals of adjacent sound fields interfere with each other in the 2.4 GHz public frequency band. Especially in areas with dense electromagnetic noise, the speech clarity drops sharply. At the same time, the private control protocols of speakers from different brands are not compatible with each other, and users are forced to manually configure the communication parameters of each device, with high operation complexity and easy to cause protocol conflicts.

[0004] Therefore, there is an urgent need for a wireless speaker group collaborative control solution that can integrate dynamic sound field adaptation, high-concurrency command scheduling, anti-interference transmission, and cross-brand compatibility to break through the bottleneck of the prior art. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a method and system for collaborative control of a wireless speaker group based on an external Bluetooth transmitting and receiving array.

[0006] To achieve the above object, the technical solution of the present invention is as follows:

[0007] In a first aspect, the present invention discloses a method for collaborative control of a wireless speaker group based on an external Bluetooth transmitting and receiving array, comprising the following steps:

[0008] S1. Obtain user dynamic position data, system load data, and environmental interference data, where:

[0009] The user dynamic position data is obtained by fusing and correcting an ultra-wideband (UWB) positioning base station and Bluetooth signal strength indication (RSSI) fingerprint data, and the correction model is

[0010] The environmental interference data is collected in real time by a spectrum scanning module of the external Bluetooth array;

[0011] S2. Based on the user dynamic position data, use an improved K-means clustering algorithm to divide the user activity area, generate a dynamic sound field partition, and dynamically adjust the physical topology connection path of the external Bluetooth array according to the environmental interference data;

[0012] S3. When the user density change rate exceeds a preset first threshold, the user cluster center offset distance exceeds a preset second threshold, or the environmental interference intensity exceeds a preset third threshold, trigger sound field reconstruction;

[0013] S4. According to the sound field reconstruction result, control the directional antenna module of the external Bluetooth array to switch to the narrow beam mode, and hierarchically process the real-time control instruction priority queue based on a multi-user priority arbitration mechanism, where:

[0014] High-priority instructions are directly sent to the edge gateway for execution, and low-priority instructions are stored in a circular buffer and processed by time slice polling;

[0015] The multi-user priority arbitration mechanism dynamically assigns instruction weights according to user role permissions, operation urgency, and historical operation frequencies.

[0016] In a second aspect, the present invention discloses a collaborative control system for a wireless speaker group based on an external Bluetooth transmitting and receiving array, which uses the above-mentioned method for collaborative control of a wireless speaker group based on an external Bluetooth transmitting and receiving array, and includes:

[0017] A data acquisition module, integrating a UWB positioning base station, a Bluetooth RSSI acquisition unit, and a spectrum scanning sensor, for obtaining user dynamic position data, system load data, and environmental interference data;

[0018] A data processing module: used to execute dynamic sound field partition calculation, environmental interference evaluation, and multi-user arbitration logic;

[0019] A control execution module: supporting directional beamforming, private channel switching, and cross-brand device protocol conversion;

[0020] A relay routing management unit, which is used to automatically switch to a standby node when the signal path is interrupted;

[0021] A virtual device interface pool, which stores instruction mapping rules for speakers of different brands and supports plug-and-play access

[0022] Among them, the external Bluetooth array includes multiple Bluetooth modules supporting beam steering, and the operating frequency band covers the 2.402GHz - 2.480GHz standard channel and the 2.412GHz ± 1MHz anti-interference private channel.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] 1. The present invention combines UWB high-precision positioning with Bluetooth RSSI fingerprint data to construct an error compensation model, overcomes the positioning drift problem of a single technology in an occluded environment, realizes centimeter-level real-time tracking of the user's position, and at the same time dynamically senses environmental interference through spectrum scanning, providing accurate data support for sound field reconstruction. Compared with the traditional fixed partition scheme, this technology can dynamically adjust the sound field coverage range according to the crowd density and interference intensity, improve the sound field matching accuracy, and effectively avoid problems such as sound overflow or blind spots in scenarios such as shopping malls and outdoor performances.

[0025] 2. Through the improved K-means clustering algorithm and multi-user priority arbitration model, efficient scheduling of high-concurrency instructions and resource optimization are achieved. The clustering radius is dynamically adjusted based on the user's movement speed and density, solving the partition lag of the traditional clustering algorithm in a dynamic scenario, and shortening the response time of sound field reconstruction. Combining the priority score calculation model (integrating permission level, operation urgency, and historical behavior), the system can intelligently allocate instruction processing resources. In a scenario with tens of thousands of concurrent users, high-priority instructions (such as emergency mute) can be responded to in a timely manner, and low-priority instructions are batch-processed through a circular buffer, improving the overall throughput of the system and greatly reducing the instruction loss rate.

[0026] 3. Through cross-brand protocol conversion and private channel dynamic preemption technology, the technical barrier of heterogeneous device collaboration is broken through. By reverse-analyzing the control instructions of the target device and encapsulating them as virtual interfaces, plug-and-play access to speakers of mainstream brands is supported, improving the success rate of protocol conversion. At the same time, based on real-time spectrum analysis, the private anti-interference channel (2.412GHz ± 1MHz) is dynamically enabled, and in an area where Wi-Fi and Bluetooth signals are mixed, the voice signal-to-noise ratio is improved, reducing the crosstalk risk compared with the traditional omnidirectional broadcast scheme. These innovations make this technology widely applicable in multiple scenarios such as home entertainment, commercial exhibitions, and outdoor performances, filling the gaps in the prior art in terms of dynamic collaboration and cross-brand compatibility. Description of the Drawings

[0027] The disclosure of the present invention will be described with reference to the accompanying drawings. It should be understood that the drawings are only for illustrative purposes and are not intended to limit the scope of protection of the present invention. In the drawings, the same reference numerals are used to refer to the same components. Among them:

[0028] Figure 1 is the step flow chart of the present invention;

[0029] Figure 2 is the step flow chart of the S1 cross-brand device compatibility processing of the present invention;

[0030] Figure 3 is the functional schematic diagram of the system module of the present invention. Detailed implementation manners

[0031] It is easy to understand that according to the technical solution of the present invention, without changing the essence of the present invention, those of ordinary skill in the art can propose various structural ways and implementation ways that can be mutually replaced. Therefore, the following detailed implementation manners and the accompanying drawings are only exemplary descriptions of the technical solution of the present invention, and should not be regarded as the whole of the present invention or regarded as a limitation or restriction on the technical solution of the present invention.

[0032] Application overview:

[0033] In the prior art, the cooperative control of a wireless speaker group mostly relies on a fixed topology connection or a single Bluetooth master-slave protocol, making it difficult to balance the dynamic sound field adaptation and high-concurrency control requirements. In traditional methods, when the user distribution changes suddenly or the environmental interference intensifies, the sound field partition and the user activity area are mismatched, resulting in volume overflow or coverage blind spots. The existing solutions lack a multi-source data fusion mechanism and cannot real-time perceive the impact of user position changes on sound field coverage. Especially in scenarios such as large commercial exhibitions, the problems of instruction congestion and signal crosstalk caused by frequent operations of multiple users are prominent, and the system response delay generally exceeds 500 ms, seriously restricting the use experience.

[0034] To solve the above problems, the inventor found that there is a strong correlation between the user density distribution and the Bluetooth signal propagation path loss. By establishing a coupled model of dynamic sound field partition and load prediction, resource optimization scheduling is realized. During the research process, it was found that UWB positioning data has high accuracy in short-distance occlusion scenarios but is vulnerable to multipath interference, while Bluetooth RSSI fingerprint data has a wide coverage range but has gradient ambiguity. Therefore, an error compensation model that fuses the two is proposed. Further verified by experiments, the user motion vector and real-time spectrum interference data are introduced into the sound field reconstruction trigger mechanism to form a closed-loop feedback control.

[0035] Specifically, the system first synchronously collects UWB positioning coordinates, Bluetooth RSSI gradients, and environmental spectrum interference data. Through an improved K-means clustering algorithm, the clustering radius is dynamically adjusted based on the user's movement speed and density to generate a sound field partition that matches the user's activity area. When the detected user density change rate exceeds the threshold or the interference intensity surges, the system automatically switches to the narrow beam directional transmission mode and classifies and processes control instructions according to the multi-user priority arbitration model (combining role permissions, operation urgency, and historical behavior): high-priority instructions (such as emergency mute) are directly passed to the edge gateway for response with a delay ≤ 80 ms; low-priority instructions (such as volume fine-tuning) are stored in the circular buffer and polled for processing in 20-ms time slices. At the same time, by reverse-analyzing the control protocols of cross-brand devices and encapsulating them into a virtual interface pool, plug-and-play access to non-native devices is realized.

[0036] Compared with the prior art, the traditional solution relies on static sound field configuration and lacks anti-interference optimization, which is prone to sound field imbalance and instruction loss in dynamic scenarios. This solution innovatively integrates multi-source positioning data and spectrum sensing technology, and realizes precise sound field energy delivery and instruction load peak shaving through dynamic beamforming and priority arbitration mechanisms. Different from traditional Bluetooth group control solutions, this technology can intelligently switch to a private anti-interference channel (2.412 GHz ± 1 MHz) according to the real-time environmental interference intensity, and is compatible with mainstream brand devices through a protocol conversion table, significantly improving the system stability and significantly reducing the instruction loss rate in scenarios with tens of thousands of concurrent users.

[0037] Through the above technical solutions, this application effectively solves the problem of dynamic collaborative control of wireless speaker groups in complex environments. The fusion positioning mechanism of UWB and Bluetooth RSSI reduces the position error in dynamic scenarios to ±0.3 meters, the improved clustering algorithm improves the matching degree of the sound field partition, and the closed-loop feedback model ensures the parameter self-optimization ability for long-term operation. This method provides a highly reliable and low-latency group audio control solution for scenarios such as commercial exhibitions and outdoor performances, significantly expanding the application boundary of the wireless speaker system.

[0038] After introducing the basic concept of the present invention, the embodiments of the present invention will be specifically introduced below with reference to the accompanying drawings.

[0039] Embodiment 1:

[0040] As Figure 1 shown, a method for collaborative control of a wireless speaker group based on an external Bluetooth transceiver array includes the following steps:

[0041] A method for collaborative control of a wireless speaker group based on an external Bluetooth transceiver array, characterized in that it includes the following steps:

[0042] S1. Obtain user dynamic position data, system load data, and environmental interference data, where:

[0043] The user's dynamic position data is obtained by fusing and correcting the ultra-wideband (UWB) positioning base station and the Bluetooth signal strength indication (RSSI) fingerprint data. The correction model is

[0044] The environmental interference data is collected in real time through the spectrum scanning module of the external Bluetooth array.

[0045] In step S1, through multi-source data fusion and real-time acquisition technology, it provides basic input for subsequent sound field zoning and topology adjustment. The specific implementation is as follows:

[0046] 1. Acquisition of user's dynamic position data:

[0047] Deployment of UWB positioning base stations: At least 4 UWB positioning base stations (working frequency band 6.5 GHz - 8.5 GHz, positioning accuracy ±10 cm) are deployed in the target area (such as a commercial performance venue). The base stations synchronize clock signals through a wired network to form a positioning grid covering the whole field. The UWB positioning base station is a positioning device based on ultra-wideband technology, and realizes centimeter-level positioning through time-of-flight ranging (ToF).

[0048] Collection of Bluetooth RSSI fingerprint data: The surrounding Bluetooth signals are scanned in real time through the receiving module in the external Bluetooth array, and the RSSI (Received Signal Strength Indication) values at each position point are recorded to generate an RSSI fingerprint database. The RSSI fingerprint database is a pre-generated signal strength - position mapping table, which is used for offline matching and online correction of Bluetooth positioning.

[0049] Data fusion and error correction: The UWB positioning coordinates (x UWB , y UWB ) and the Bluetooth RSSI fingerprint data are jointly calibrated, and the positioning error is corrected through the following model:

[0050]

[0051] Among them, α = 0.6, β = 0.4 are the measured calibration coefficients (fitting the on-site calibration data through the least squares method);

[0052] σ UWB is the UWB positioning variance (reflecting the signal stability of the base station);

[0053] is the gradient of the Bluetooth signal strength changing with distance.

[0054] Output the corrected user coordinates (x', y') and the motion vector (speed v, direction θ).

[0055] 2. System load data collection

[0056] Historical operation log analysis: Extract historical control command records (such as volume adjustment and sound field switching commands) from the edge gateway and count the following indicators:

[0057] User operation frequency: the number of command triggers per unit time (e.g. 10 times / minute);

[0058] Device response delay: the average time from when the command is sent to when the speaker responds (e.g. 150ms);

[0059] User density correlation model: Based on the K-means clustering results, a correlation model between user clustering areas and instruction volume is established (e.g., the instruction volume in high-density areas accounts for ≥ 70%).

[0060] Real-time load prediction: Using the sliding window statistical method (window size 10 seconds), the peak load within the next minute is predicted based on the current instruction growth rate. The calculation formula is: Q predict =Q current +k·ΔQ / Δt

[0061] Where k=0.8 is the attenuation factor, and ΔQ / Δt is the rate of change of the command amount.

[0062] Sliding window statistics is a real-time data stream processing method that predicts future trends through statistics (such as mean and variance) within a fixed time window.

[0063] 3. Environmental interference data collection

[0064] The spectrum scanning module is configured as follows: an external Bluetooth array integrated spectrum analysis unit, which scans the 2.4GHz-2.4835GHz frequency band with a period of 100ms and collects the following parameters:

[0065] Electromagnetic noise intensity: background noise power of each channel (e.g. -90dBm to -70dBm);

[0066] Channel occupancy rate: the proportion of time each channel is occupied by Wi-Fi and Bluetooth devices (e.g. 30% to 80%).

[0067] Interference feature extraction: High-interference channels are marked through threshold judgment (such as noise intensity > -80dBm or channel occupancy > 50%).

[0068] The collected data is integrated and preprocessed, and the UWB, Bluetooth RSSI and spectrum scanning data are aligned by time stamp to ensure data consistency; data beyond the physical range is eliminated (such as UWB coordinates beyond the site boundary, RSSI mutation exceeds 20dBm); the original data is temporarily stored in the ring buffer of the edge gateway for subsequent processing modules to call.

[0069] Compared with traditional technologies, traditional methods for group control of wireless speakers usually rely on a single positioning technology (such as Bluetooth RSSI or UWB independent positioning), which is prone to large positioning errors due to signal attenuation, multipath effects, or environmental interference. For system load processing, static thresholds or fixed priority allocations are commonly used, making it difficult to adapt to dynamic user density and scenarios with sudden instructions. In response to environmental interference, it is limited to passive avoidance or simple channel switching, lacking active perception and real-time optimization of complex electromagnetic environments. In addition, problems such as poor cross-brand device compatibility and multi-user instruction conflicts further limit the flexibility and stability of the system. This solution effectively solves technical problems such as high-precision positioning, flexible resource allocation, and robustness in complex environments through multi-source data fusion (joint correction of UWB and Bluetooth RSSI), dynamic load prediction (sliding window statistics and real-time instruction grading), and a spectrum scanning-driven interference avoidance mechanism, providing a systematic optimization solution for the collaborative control of speaker groups in multiple scenarios.

[0070] Through the above technical solutions, this application realizes the intelligent collaborative control of wireless speaker groups, significantly improving the system response accuracy and stability in complex scenarios. By fusing UWB positioning and Bluetooth RSSI fingerprint data, the system accurately captures the user's position and movement trend in a dynamic environment, providing a highly reliable spatial reference for sound field zoning. Combining real-time spectrum scanning and interference feature extraction, it dynamically adjusts the physical topology and channel strategy to ensure the continuity and reliability of signal transmission in electromagnetic interference scenarios. At the same time, based on the load grading mechanism predicted by the user operation history and sliding window, collaborating with the edge gateway and circular buffer, it optimizes the real-time processing efficiency of high-concurrency instructions. Each module forms a closed loop through data alignment, anomaly filtering, and cache interaction, ultimately achieving full-link adaptive collaboration from data acquisition to execution control, providing low-latency and highly compatible group control capabilities for multi-user intensive scenarios such as commercial performances and conferences.

[0071] S2. Based on the user's dynamic position data, use an improved K-means clustering algorithm to divide the user activity area, generate a dynamic sound field partition, and dynamically adjust the physical topology connection path of the external Bluetooth array according to the environmental interference data;

[0072] The improved K-means clustering algorithm in step S2 includes:

[0073] Dynamically adjust the clustering radius r according to the average user movement speed and real-time density ρ, where:

[0074]

[0075] When the distance between adjacent cluster centers is less than 0.5r, automatically merge them into the same sound field partition.

[0076] The specific implementation of step S2 is as follows:

[0077] The improved K-means clustering algorithm inputs the corrected user coordinates (x', y') and motion vector (velocity v avg , direction θ) data generated in step S1. The clustering radius r is dynamically adjusted according to the average user velocity v avg and the real-time density ρ. When the user moves quickly (v avg > 1 m / s), the radius is enlarged to cover the motion trajectory; in high-density areas (ρ ≥ 5 people / m 2 ), the radius is reduced to improve the partitioning accuracy. If the distance between the centers of adjacent clustering clusters is less than 0.5r, they are automatically merged into the same sound field partition. Merging example: when the distance between the centers of two clustering clusters is 0.4 m (when r = 1.0 m), the coverage after merging is expanded to a radius of 1.2 m.

[0078] The dynamic sound field partitioning logic is to map the clustering results to the physical space, generate polygonal sound field partitions (such as the commercial performance stage area, audience area A / B), and assign independent speaker groups to each partition. The method of dynamically adjusting the clustering radius can more flexibly adapt to different user distributions and motion conditions, making the sound field partitioning more reasonable and accurate.

[0079] The improved K-means clustering algorithm is an extended version of the traditional K-means. It adapts to user mobility and spatial density through dynamic radius and merging rules, and solves the problems of over-segmentation or under-segmentation caused by a fixed clustering radius. The Dijkstra algorithm is a classic shortest path algorithm, which is used in this solution to select the relay path with the lowest signal transmission delay and the least interference. The relay routing management unit is a hardware module responsible for monitoring the link quality and performing path switching, and supports forward error correction coding (FEC) to reduce the packet loss rate.

[0080] Compared with traditional technologies, traditional user activity area partitioning technologies mostly rely on fixed parameters and static algorithm models, and often cannot be flexibly adjusted according to factors such as users' real-time dynamic data and environmental changes. Their main defects lie in poor adaptability to complex and changeable actual scenarios, inaccurate partitioned areas, and being easily affected by environmental interference and dynamic changes in user behavior, resulting in a series of subsequent operations (such as resource allocation, personalized services, etc.) based on this area partition being difficult to achieve ideal effects. However, this solution can dynamically and accurately partition the user activity area through the improved K-means clustering algorithm based on users' real-time dynamic data and environmental interference conditions, effectively solving the technical problems of inflexible, inaccurate, and easily interfered area partitioning in traditional technologies.

[0081] Through the above technical solution, the present application realizes the dynamic and accurate division of the user's activity area. Based on the user's real-time dynamic data and the environmental interference situation, the improved K-means clustering algorithm is used to flexibly adjust parameters such as the clustering radius, making the divided dynamic sound field area more in line with the actual situation. By mapping the clustering results to the physical space to form a reasonable and accurate polygonal sound field area, and assigning independent speaker groups to each partition, the reasonable allocation of resources and personalized service configuration are realized. Each module cooperates with each other. The user dynamic data acquisition module provides real-time and accurate input for the K-means clustering algorithm module. The clustering algorithm module performs dynamic calculations based on the set rules and real-time data and outputs a reasonable area division result. The mapping module then converts this result into the sound field area division in the physical space. The speaker group allocation module finally makes corresponding configurations according to the division result, overall improving the accuracy and rationality of the related operations based on the division of the user's activity area.

[0082] S3. When the user density change rate exceeds the preset first threshold, the user cluster center offset distance exceeds the preset second threshold, or the environmental interference intensity exceeds the preset third threshold, trigger the sound field reconstruction.

[0083] In step S2, dynamically adjust the physical topology connection path of the external Bluetooth array according to the environmental interference data, where dynamically adjusting the physical topology connection path includes: when the environmental interference intensity exceeds the preset third threshold, switch to the standby relay node through the relay routing management, and select the signal transmission path based on the shortest path algorithm, and at the same time reduce the transmission power of the Bluetooth array in the non-target area to 40%.

[0084] The relay routing management includes: real-time monitoring the link quality of the external Bluetooth array, and when the packet loss rate exceeds 5% or the signal strength is lower than -85dBm, perform the following operations:

[0085] Select the standby relay node based on the Dijkstra algorithm, and preferentially select the node with a channel occupancy rate lower than 30%;

[0086] Enable forward error correction coding (FEC) for data transmission on the switched path;

[0087] The external Bluetooth array in the non-target area switches to the sleep mode.

[0088] In the present application, the definition of the preset threshold is based on the statistical data of the scene measurement and the sound field coverage performance optimization model. The specific method is as follows:

[0089] 1. Preset the first threshold (user density change rate)

[0090] Definition basis: The user density change rate (ΔD) refers to the percentage increase or decrease of the number of users per unit area per unit time. The calculation formula is:

[0091]

[0092] Among them, D t is the user density at the current moment, and D t-Δt is the density in the previous time window (usually set to 30 seconds). Threshold calibration: Through the analysis of measured data in multiple scenarios, when ΔD ≥ 30% / minute, the uniformity of the sound field coverage (standard deviation) drops by more than 40%, and reconstruction needs to be triggered. This threshold is verified through Monte Carlo simulation, balancing the response speed and the false trigger rate.

[0093] 2. Preset the second threshold (distance of the user cluster center deviation)

[0094] Definition basis: The distance of the user cluster center deviation (L) refers to the Euclidean distance between the center point of the current user cluster and the center point of the initial sound field partition.

[0095] Threshold calibration: Set according to the coverage radius (R) of the sound field partition. Usually, take L threshold = 0.6R. For example, when the partition coverage radius is 5 meters, L threshold = 3 meters. Verified through the beam width (θ) and the projection distance (d): If L > d·tan(θ / 2), the original beam cannot cover the new cluster. For example, when θ = 15° and d = 10 meters, the offset threshold is set to 2.68 meters (≈10×tan7.5°), rounded up to 3 meters.

[0096] 3. Preset the third threshold (environmental interference intensity)

[0097] Definition basis: The environmental interference intensity (I) is comprehensively evaluated through the Bluetooth channel occupancy rate (C) and the noise power (N):

[0098]

[0099] Among them, C max is the maximum available occupancy rate of the Bluetooth channel (100% when there are 79 channels), and N max is the noise power threshold (-80dBm). Threshold calibration: When I ≥ 0.6, the speech signal-to-noise ratio (SNR) drops below 8dB, triggering anti-interference measures. This value is verified through Wi-Fi / Bluetooth coexistence experiments to ensure that the bit error rate (BER) is lower than 1e -5 .

[0100] Dynamic adjustment mechanism (the threshold can be dynamically optimized according to the scenario type): High-sensitivity scenarios (such as emergency evacuation): The threshold is lowered by 20% (ΔD ≥ 24% / minute, L ≥ 2.4 meters, I ≥ 0.48); Anti-interference priority scenarios (such as industrial exhibition areas): The threshold is raised by 15% (I ≥ 0.69).

[0101] Step S3 triggers sound field reconstruction and executes corresponding control strategies by dynamically monitoring user behavior and environmental interference status. Based on the latest user location data, the improved K-means clustering algorithm is re-executed to merge or split adjacent clustering clusters, generating new sound field partition boundaries. If the user density suddenly increases and causes the original partitions to overlap, adjacent clusters are merged and the partition range is expanded.

[0102] When the environmental interference intensity in Step S1 exceeds the preset value, the physical topology connection path is adjusted. When the environmental interference intensity exceeds the preset third threshold, a standby relay node is selected through the relay routing management unit. The specific rules include: preferentially selecting nodes with a channel occupancy rate < 30% and a signal strength > -80 dBm; using the Dijkstra algorithm to calculate the shortest transmission path to ensure that the end-to-end delay ≤ 50 ms. The Dijkstra algorithm is a classic algorithm for finding the shortest path in a weighted graph and is used in the present invention to select the optimal node among multiple standby relay nodes for route switching; forward error correction coding (FEC) is enabled for data transmission on the switched path and the redundant data accounts for 20%. Forward error correction coding is a technology that automatically corrects transmission errors by adding redundant data during data transmission, and the accuracy of data transmission is ensured by setting the redundant data ratio to 20%; the transmit power is dynamically adjusted, and the external Bluetooth array in the non-target area (such as the unactivated partition in the back row of the auditorium) is switched to the sleep mode, reducing its transmit power to 10 mW. This can reduce the energy consumption of the Bluetooth array in the non-target area and reduce its potential interference to other devices while ensuring normal communication in the target area; the transmit power of the Bluetooth array in the non-target area is reduced to 40%, focusing the energy on the target area.

[0103] Compared with traditional technologies, traditional sound field control systems mostly rely on fixed thresholds and static topology configurations, and it is difficult to respond to the dynamic changes of user density and complex electromagnetic interference environments in real time. Its defects are: when the user cluster deviates or the environmental interference exceeds the limit, the sound field partition cannot be adaptively adjusted, resulting in coverage blind spots or signal overlaps; the relay path selection mostly uses fixed routing or simple polling strategies, and it is difficult to balance the transmission delay and anti-interference requirements; noise suppression relies on preset channel avoidance and lacks a comprehensive evaluation of real-time spectrum occupancy and noise power. This solution solves technical bottlenecks such as lagging sound field reconstruction, insufficient transmission stability, and poor multi-scenario adaptability through dynamic threshold calibration (based on the user density change rate, cluster deviation distance, and environmental interference intensity), relay path optimization driven by the Dijkstra algorithm, and the collaborative mechanism of forward error correction coding and beamforming.

[0104] Through the above technical solutions, the present application realizes the intelligent dynamic reconstruction of sound field zoning and high-reliability signal transmission in complex scenarios. By real-time monitoring of the changes in user density and cluster offset, combined with an improved clustering algorithm, the system dynamically adjusts the boundaries of the sound field zoning to ensure an accurate match between the sound field coverage and the user distribution; the multi-dimensional assessment of the environmental interference intensity triggers anti-interference strategies. Through spectrum sensing and relay path optimization, in collaboration with forward error correction coding and beamforming technologies, the impact of multipath effects and interference in non-target areas on the transmission quality is significantly reduced. Each module operates in a closed-loop based on real-time data interaction: the threshold calibration module dynamically adapts to the scene requirements, the relay routing management module dynamically selects the optimal path based on the link quality, and the power control module synchronously adjusts the energy consumption in non-target areas. Finally, an all-link adaptive collaboration from environmental perception to execution optimization is formed, providing low-latency and high-robustness sound field control capabilities for dynamic scenarios such as commercial performances and industries.

[0105] S4. According to the sound field reconstruction result, control the directional antenna module of the external Bluetooth array to switch to the narrow beam mode, and hierarchically process the priority queue of real-time control instructions based on the multi-user priority arbitration mechanism, where:

[0106] High-priority instructions are directly sent to the edge gateway for execution, and low-priority instructions are stored in the circular buffer and processed by time slice polling;

[0107] The multi-user priority arbitration mechanism dynamically assigns instruction weights according to user role permissions, operation urgency, and historical operation frequencies.

[0108] The edge gateway architecture uses a Raspberry Pi CM4 module as the edge computing node, runs a lightweight real-time operating system (such as FreeRTOS), supports the direct passage of high-priority instructions, with a response delay ≤ 100 ms, and directly sends them to the target speaker; supports protocol encapsulation, converts control instructions into Bluetooth HCI protocol packets, and transmits them to the external array through the SPI interface; supports private channel switching. When interference on the standard channel (2.402 GHz - 2.480 GHz) is detected, it switches to a 2.412 GHz ± 1 MHz private channel and broadcasts a synchronization beacon.

[0109] The circular buffer is processed by polling in time slices, which means that within each time slice, the data in the circular buffer is processed. In each time slice, a part of the data is taken out from the circular buffer for processing. After the processing is completed, wait for the next time slice to arrive and then continue to process the subsequent data. This can ensure the orderly and efficient processing of the data in the circular buffer, and at the same time avoid a certain data processing task occupying resources for a long time and affecting the processing of other data. The circular buffer management adopts a circular queue (with a capacity of 50 instructions) and polls to process low-priority instructions in time slices (20 ms); if the buffer is full, discard the oldest low-score instructions (Score < 0.4) and record the log; merge the same type of instructions (such as consecutive volume +5% requests) into a single instruction to reduce redundant transmission.

[0110] The beam width of the narrow beam pattern described in step S4 is negatively correlated with the user density, specifically satisfying:

[0111]

[0112] If the environmental interference intensity exceeds -80 dBm, then on this basis, θ is reduced by 10%, and the final beam width θ is not less than 10°;

[0113] The user density is calculated by the ratio of the number of UWB tags to the sound field partition area.

[0114] Based on the sound field reconstruction result, step S4 optimizes signal transmission through the narrow beam pattern and combines a multi-user arbitration mechanism to achieve real-time hierarchical processing of instructions. The directional antenna module of the external Bluetooth array adopts a phased array design (such as the Nordic nRF5340 chipset), which supports dynamic adjustment of the beam width θ in the range of 10° to 30°; an interference compensation mechanism is adopted. If the environmental interference intensity exceeds -80 dBm (detected in real time by the spectrum scanning module), then θ is further reduced by 10%, but not less than 10° at the lowest. In a high-interference environment, appropriately further reducing the beam width helps to improve the anti-interference ability and transmission accuracy of the signal, etc. The beam pointing is controlled according to the user clustering center coordinates, and the optimal transmission angle is calculated through the direction-of-arrival estimation algorithm (such as the MUSIC algorithm) to control the antenna phase offset.

[0115] The user density ρ is calculated by the ratio of the number of UWB tags to the sound field partition area. The UWB (Ultra WideBand) technology has characteristics such as high-precision positioning. By counting the number of UWB tags in a specific sound field partition and combining the area of this partition, the user density situation in this area can be calculated more accurately.

[0116] In crowded areas, narrow beams (θ = 15°) are used to reduce signal scattering interference; in low-density areas, wider beams (θ = 20°) are used to expand the coverage range. This helps to optimize resource allocation and signal transmission performance in scenarios with different user densities.

[0117] The specific implementation of the multi-user priority arbitration mechanism described in step S4 includes:

[0118] Receive instruction requests from multiple control terminals, and extract the user role tags (administrator / ordinary user), operation types (emergency mute / volume adjustment), and operation timestamps of the instruction sources.

[0119] Calculate the instruction priority score according to preset rules:

[0120]

[0121] If there are conflicting instructions with a score difference less than 0.1 within the same group, push a negotiation confirmation interface to the user with the lower score.

[0122] In a multi-user environment for instruction reception, it is necessary to receive instruction requests from multiple control terminals. These control terminals may include different management terminals, ordinary user terminals, etc.

[0123] After receiving the instruction request, the system extracts important parameters from it, including the user role tag (divided into administrator and ordinary user) of the instruction issuer, operation types (such as emergency mute operation, volume adjustment operation, etc.), and operation timestamp. These parameters are crucial for subsequent priority calculation and arbitration.

[0124] Calculate the instruction priority score according to preset rules, where:

[0125] Administrators usually have a higher permission level, for example, it can be set to 1, while ordinary users have a relatively lower permission level, which can be set to 0.5, etc. The higher the permission level, the greater the weight in priority calculation, which reflects the degree of emphasis on administrator operations.

[0126] For different operation types, their urgency coefficients are different. For example, the urgency coefficient of the emergency mute operation can be set to 1 because it may involve some emergency situations that require a quick response; while for relatively less urgent operations such as volume adjustment operations (step size ≤ 5%), their urgency coefficients can be set to 0.3, etc. The setting of the urgency coefficient helps to distinguish the importance and urgency of different operations.

[0127] The timestamp delay of an operation refers to the time delay from when an instruction is issued until the system receives and starts processing the instruction. The threshold delay is a preset time value, which can be set to 500 ms, for example. The smaller the timestamp delay, that is, the more timely the instruction processing, the greater the contribution of this item in the priority score calculation, which encourages operations with quick responses.

[0128] If there are conflicting instructions with a score difference less than 0.1 within the same group, a negotiation confirmation interface is pushed to the user with a lower score. When the priorities of two instructions are very close, simply executing according to the priority may result in the failure to meet the reasonable needs of some users. By pushing the negotiation confirmation interface, relevant users can communicate and confirm further to make a more reasonable operation decision. In a commercial performance, the "emergency mute" instruction initiated by the stage administrator (Score ≈ 1.0) can preempt the "volume adjustment" instruction of the audience side (Score ≈ 0.5) to ensure a quick response to performance accidents.

[0129] The classification of the high-priority instructions and the low-priority instructions described in step S4 includes:

[0130] High-priority instructions: sound field switching instructions, emergency mute instructions, cross-brand device access requests, system fault warning instructions;

[0131] Low-priority instructions: volume adjustment instructions (step ≤ 5%), device status query instructions, ambient light sensing synchronization instructions;

[0132] The high-priority instructions are directly sent down through the edge gateway, and the response delay ≤ 100 ms; the low-priority instructions are stored in the circular buffer and processed in batches according to a 20-ms time slice for polling.

[0133] Among the high-priority instructions: The sound field switching instruction means that in some complex communication or multimedia scenarios, it may be necessary to quickly switch between different sound fields or channels, etc. The high priority of the sound field switching instruction ensures that this switching operation can be executed in a timely manner to avoid affecting the continuity of relevant services, etc. The emergency mute instruction means that when there are some sudden noise interferences or the need to immediately mute, the high priority of the emergency mute instruction ensures that it can take effect quickly, such as in the scenario where a harsh noise suddenly appears in a meeting room, etc. The cross-brand device access request means that in an environment where multi-brand devices coexist, the timely processing of the cross-brand device access request helps to quickly integrate different device resources, etc., so it is given a high priority. The system fault warning instruction means that the high priority of the system fault warning instruction ensures that the fault information can be processed and responded to in the first time, so as to conduct fault troubleshooting and repair in a timely manner, etc.

[0134] High-priority instructions are directly issued through the edge gateway, with a response delay ≤ 100 ms. The edge gateway performs operations such as data processing and instruction forwarding on the network edge side close to the data source or the user side. In this way, the delay of instruction transmission and processing can be greatly reduced, ensuring the fast response of high-priority instructions.

[0135] Among the low-priority instructions, the volume adjustment instruction (step size ≤ 5%) has a relatively low requirement for the immediacy of the system compared to operations such as emergency muting. Therefore, its priority is relatively low. The device status query instruction is mainly used to obtain some operating status information of the device, etc., and generally does not require an immediate response, so it belongs to the low-priority instruction. The ambient light sensing synchronization instruction is mainly used to adjust some displays or other related settings according to the ambient light conditions, and it has a low requirement for real-time performance.

[0136] Low-priority instructions are stored in the circular buffer and processed in batches according to a 20-ms time slice. This can orderly process these low-priority instructions without affecting the fast response of high-priority instructions, improving the overall instruction processing efficiency of the system.

[0137] Example (commercial performance):

[0138] Scenario 1: Emergency mute trigger:

[0139] When the stage manager issues an "emergency mute" instruction:

[0140] The edge gateway directly interrupts the current audio stream and sends a mute instruction to the external array;

[0141] The external array switches to the private channel and transmits to the stage speakers through a narrow beam (θ = 10°) to avoid accidental triggering of devices in the audience area;

[0142] Low-priority instructions in the circular buffer (such as a volume adjustment request from a certain audience) are temporarily stored and executed in order after the mute is lifted.

[0143] Scenario 2: Multi-area sound field synchronization:

[0144] When the user cluster moves from the main stage to the VIP lounge:

[0145] The dynamic sound field partition merges the original VIP area and the moving cluster, triggering a beam width adjustment (θ from 20° → 15°);

[0146] The external array establishes a low-latency transmission path through the relay node (channel occupancy rate < 30%) to synchronize the playback content.

[0147] Compared with traditional technologies, traditional sound field control systems mostly rely on static beam configurations and fixed-priority instruction processing mechanisms, making it difficult to adapt to dynamic user distributions and complex electromagnetic environments. Their deficiencies are as follows: The fixed beam width leads to increased signal interference in user-dense areas and insufficient coverage in sparse areas; the instruction processing adopts a single-priority rule, unable to distinguish user roles and operation urgency, easily causing multi-user instruction conflicts or delayed responses to critical operations; the anti-interference strategy is limited to passive avoidance, lacking real-time spectrum sensing and dynamic channel optimization capabilities. This solution addresses core issues such as uneven signal coverage, instruction response delays, and insufficient anti-interference capabilities in multiple scenarios through dynamic beam width adjustment (based on user density and environmental interference intensity), multi-dimensional priority arbitration (integrating role permissions, operation urgency, and historical behavior), and a collaborative processing mechanism between the edge gateway and the circular buffer.

[0148] Through the above technical solutions, this application realizes the intelligentization and adaptive optimization of the sound field control system in complex scenarios. The sound field reconstruction module dynamically adjusts the beam width according to user density, enhances the signal intensity in dense areas through narrow-beam focusing, and expands the coverage of sparse areas with wide beams to ensure precise matching of the sound field distribution with user activities; the multi-user arbitration mechanism combines role permissions and operation semantics to dynamically allocate instruction priorities, ensuring millisecond-level responses to emergency operations (such as muting, fault alarms), and at the same time orderly scheduling low-priority instructions through the circular buffer to balance real-time performance and processing efficiency. The environment perception module monitors spectrum interference in real time, drives relay path optimization and forward error correction coding, coordinates private channel switching and power adjustment, and significantly improves signal transmission stability. Each module collaborates in a closed loop with the data stream as the link: the sound field partition drives the beam direction, the priority arbitration connects the edge gateway and the buffer, and the environment perception feedbacks the anti-interference strategy, finally forming a full-link adaptive system from dynamic perception to precise execution, providing low-latency and high-reliability group control capabilities for high-concurrency scenarios such as commercial performances and conferences.

[0149] As Figure 2 shown, step S1 also includes cross-brand device compatibility processing:

[0150] Scan the broadcast packets of surrounding Bluetooth devices and extract the manufacturer ID and protocol version;

[0151] If a non-natively supported device is detected, call the preset protocol conversion table to map its control instructions to a standard instruction set, including:

[0152] Send a test instruction set to the target device and record the function fields in its response data packet;

[0153] Perform response validity detection on the mapped standard instructions. If the device does not respond, switch to the preset general instruction library;

[0154] Record the instruction eigenvalue that cannot be mapped and generate an error log.

[0155] The protocol conversion table is generated by reverse parsing the control instructions of the target device, specifically including:

[0156] Extract the instruction encoding rules for volume adjustment, play control, and sound field mode, and encapsulate them into a virtual control interface.

[0157] The cross-brand device compatibility processing involved in step S1 has an important and specific operation process. First, the manufacturer ID and protocol version are extracted by scanning the broadcast packets of surrounding Bluetooth devices, and the connected devices are initially identified and information is obtained.

[0158] When it is detected that the connected device is not natively supported, it is necessary to call the preset protocol conversion table to process its control instructions, that is, map its control instructions to a standard instruction set. This includes multiple specific sub-steps:

[0159] Send a test instruction set to the target device. After the target device receives these test instruction sets, it will return corresponding data packets, and we need to record the function fields in its response data packets. These function fields contain feedback information of the target device for various instructions and are important bases for subsequent operations such as detecting the validity of instructions.

[0160] Perform a response validity detection on the mapped standard instructions to ensure that the converted instructions can be correctly recognized and executed by the target device. If the device does not respond, it indicates that the currently mapped standard instructions may not be applicable to the target device. At this time, it is necessary to switch to the preset general instruction library. The preset general instruction library contains a series of relatively general instruction sets that can ensure basic interactions between devices in specific situations.

[0161] For those instructions that cannot be mapped, it is necessary to record their instruction characteristic values and generate error logs. This helps to analyze and improve device compatibility issues in the future. For example, the protocol conversion table can be further improved by analyzing the error logs.

[0162] The protocol conversion table is generated by reverse parsing the control instructions of the target device. The reverse parsing is assisted by machine learning. The protocol conversion table includes extracting instruction encoding rules such as volume adjustment, play control, and sound field mode. The instruction encoding rules are the internal rules that the target device follows when receiving and processing relevant control instructions. By extracting and analyzing these rules, they are encapsulated into a virtual control interface. The role of the virtual control interface is to provide a unified and standardized control channel for the interaction between different brand devices, so that in the process of cross-brand device compatibility processing, various devices can be controlled and managed in a relatively unified manner, thereby improving the compatibility between devices and the stability of interactions.

[0163] Compared with traditional technologies, traditional multi-device collaborative control systems usually rely on a single brand or a fixed protocol stack, making it difficult to achieve seamless compatibility across devices from different manufacturers. The control instruction encoding rules of devices from different brands vary greatly, and there is a lack of a general protocol conversion mechanism, resulting in unrecognizable or incorrect execution of instructions when non-native devices are connected; compatibility processing mostly uses manual configuration or limited preset rules and cannot dynamically adapt to new device types; the error handling mechanism is imperfect, making it difficult to trace the cause of instruction failure and optimize the system. This solution extracts manufacturer characteristics through broadcast packet parsing, dynamically maps the instruction set through a protocol conversion table, and uses test instruction verification and a general instruction library fallback mechanism to solve technical problems such as poor instruction compatibility, low access efficiency, and lagging error repair for cross-brand devices, achieving plug-and-play and stable control of heterogeneous devices.

[0164] Through the above technical solution, this application achieves efficient compatibility and dynamic adaptation for cross-brand device collaborative control. The protocol conversion module generates a standardized virtual interface by reverse-parsing the instruction encoding rules of the target device, mapping instructions such as volume adjustment and play control from different manufacturers into a unified instruction set; the test instruction verification mechanism actively detects the response characteristics of the device and realizes basic interaction guarantee in abnormal scenarios in combination with the general instruction library. The error log recording module captures the characteristics of unmapped instructions in real time, providing data support for the continuous optimization of the protocol conversion table. Each module forms a closed loop through device identification, instruction conversion, validity verification, and error feedback: broadcast packet parsing provides device characteristic input for protocol conversion, virtual interface encapsulation ensures instruction compatibility, test verification and log analysis drive the system to adaptively upgrade, and finally realizes full-link automatic collaboration from device access to stable control, significantly improving the flexibility and management efficiency of multi-brand device groups.

[0165] Embodiment 2:

[0166] As Figure 3 shown, a wireless speaker group collaborative control system based on an external Bluetooth transmit-receive array uses the above-mentioned wireless speaker group collaborative control method based on an external Bluetooth transmit-receive array, including:

[0167] A data acquisition module, integrating a UWB positioning base station, a Bluetooth RSSI acquisition unit, and a spectrum scanning sensor, is used to obtain user dynamic position data, system load data, and environmental interference data;

[0168] A data processing module: used to perform dynamic sound field zoning calculation, environmental interference assessment, and multi-user arbitration logic;

[0169] A control execution module: supports directional beamforming, private channel switching, and cross-brand device protocol conversion;

[0170] A relay routing management unit, used to automatically switch to a standby node when the signal path is interrupted;

[0171] A virtual device interface pool stores instruction mapping rules for speakers of different brands and supports plug-and-play access.

[0172] Among them, the external Bluetooth array includes multiple Bluetooth modules supporting beam steering, and the operating frequency band covers the 2.402GHz - 2.480GHz standard channel and the 2.412GHz ± 1MHz anti-interference private channel.

[0173] Compared with traditional technologies, traditional methods often rely on relatively single and limited-precision sensor technologies, which are not comprehensive enough in data collection and difficult to simultaneously obtain key data in multiple dimensions, such as location data, system load data, environmental interference data, etc. Moreover, in data processing, they lack comprehensive and dynamic calculation and evaluation capabilities, are difficult to effectively cope with interference in complex environments, and the multi-user arbitration logic is not perfect enough. In terms of control execution, traditional technologies lack strong support for directional beamforming, private channel switching, and cross-brand device protocol conversion, resulting in poor device compatibility and stability. At the same time, the response mechanism of traditional technologies when the signal path is interrupted is not perfect enough and cannot automatically switch to a standby node. In addition, there is a lack of unified and effective management of the instruction mapping rules for speakers of different brands. And this solution can solve many problems existing in the above traditional technologies. By integrating a variety of advanced sensors and modules, it realizes comprehensive and accurate data collection, efficient and dynamic data processing, powerful control execution capabilities, and a perfect signal management mechanism, etc.

[0174] Through the above technical solution, this application combines UWB high-precision positioning with Bluetooth RSSI fingerprint data to construct an error compensation model, overcomes the positioning drift problem of single technologies in occluded environments, realizes centimeter-level real-time tracking of user positions, and at the same time dynamically senses environmental interference through spectrum scanning to provide accurate data support for sound field reconstruction. Compared with traditional fixed-zone schemes, this technology can dynamically adjust the sound field coverage range according to the crowd density and interference intensity, improve the sound field matching accuracy, and effectively avoid problems such as sound spillage or blind spots in scenarios such as shopping malls and outdoor performances. Through the improved K-means clustering algorithm and multi-user priority arbitration model, efficient scheduling of high-concurrency instructions and resource optimization are achieved. By dynamically adjusting the clustering radius based on the user movement speed and density, the problem of partition lag of traditional clustering algorithms in dynamic scenarios is solved, and the response time of sound field reconstruction is shortened. Combined with the priority score calculation model (integrating permission level, operation urgency, and historical behavior), the system can intelligently allocate instruction processing resources. In a scenario with ten thousand-level concurrency, high-priority instructions (such as emergency mute) are timely responded to, and low-priority instructions are batch processed through a circular buffer, improving the overall throughput of the system and greatly reducing the instruction loss rate.

[0175] Through the cross-brand protocol conversion and private channel dynamic preemption technology, the technical barrier of heterogeneous device collaboration is broken through. By reverse-analyzing the control instructions of the target device and encapsulating them into a virtual interface, it supports the plug-and-play access of mainstream brand speakers and improves the protocol conversion success rate. At the same time, based on real-time spectrum analysis, a private anti-interference channel (2.412 GHz ± 1 MHz) is dynamically enabled, and in the area where Wi-Fi and Bluetooth signals are mixed, the voice signal-to-noise ratio is improved, and the crosstalk risk is reduced compared with the traditional omnidirectional broadcast scheme. These innovations make this technology widely applicable in multiple scenarios such as home entertainment, commercial exhibitions, and outdoor performances, filling the gaps in the existing technology in terms of dynamic collaboration and cross-brand compatibility.

[0176] The technical scope of the present invention is not limited to the content described above. Those skilled in the art can make various deformations and modifications to the above embodiments without departing from the technical idea of the present invention, and these deformations and modifications should all fall within the protection scope of the present invention.

Claims

1. A method for collaborative control of a wireless speaker group based on an external Bluetooth transmitting and receiving array, characterized in that: It includes the following steps: S1. Obtain user dynamic location data, system load data, and environmental interference data, where: The user's dynamic position data is obtained by fusing and correcting the ultra-wideband (UWB) positioning base station and Bluetooth signal strength indication (RSSI) fingerprint data, and the correction model is The environmental interference data is collected in real time by the spectrum scanning module of an external Bluetooth array; S2. Based on the user dynamic location data, use an improved K-means clustering algorithm to divide the user activity area, generate a dynamic sound field partition, and dynamically adjust the physical topology connection path of the external Bluetooth array according to the environmental interference data; S3. When the user density change rate exceeds a preset first threshold, the user cluster center offset distance exceeds a preset second threshold, or the environmental interference intensity exceeds a preset third threshold, trigger sound field reconstruction; S4. According to the sound field reconstruction result, control the directional antenna module of the external Bluetooth array to switch to the narrow beam mode, and classify and process the real-time control instruction priority queue based on the multi-user priority arbitration mechanism, where: High-priority instructions are directly sent to the edge gateway for execution, and low-priority instructions are stored in the circular buffer and processed by time slice polling; The multi-user priority arbitration mechanism dynamically assigns instruction weights according to user role permissions, operation urgency, and historical operation frequencies.

2. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 1, characterized in that: Step S1 further includes cross-brand device compatibility processing: Scan the broadcast packets of surrounding Bluetooth devices, and extract the manufacturer ID and protocol version; If a non-natively supported device is detected, call a preset protocol conversion table to map its control instructions to a standard instruction set, including: Send a test instruction set to the target device, and record the function fields in its response data packet; Perform response validity detection on the mapped standard instructions. If the device does not respond, switch to a preset general instruction library; Record the instruction feature values that cannot be mapped and generate an error log.

3. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 2, wherein: The protocol conversion table is generated by reverse parsing the control instructions of the target device, specifically including: Extract the instruction coding rules for volume adjustment, playback control, and sound field mode, and encapsulate them into a virtual control interface.

4. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 1, wherein: The improved K-means clustering algorithm in step S2 includes: According to the average motion speed v of the user avg and the real-time density ρ to dynamically adjust the clustering radius r, where: When the distance between adjacent cluster centers is less than 0.5r, automatically merge them into the same sound field partition.

5. The wireless speaker group collaborative control method based on an external Bluetooth transmission and reception array according to claim 1, characterized in that: The dynamic adjustment of the physical topology connection path in step S2 includes: When the environmental interference intensity exceeds the preset third threshold, switch to a standby relay node through relay route management, select a signal transmission path based on the shortest path algorithm, and at the same time reduce the transmission power of the Bluetooth array in the non-target area to 40%; 6. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 5, wherein: The relay route management includes: Real-time monitor the link quality of the external Bluetooth array. When the packet loss rate exceeds 5% or the signal strength is lower than -85dBm, perform the following operations: Select the standby relay node based on the Dijkstra algorithm, and preferentially select nodes with a channel occupancy rate lower than 30%; Enable forward error correction coding (FEC) for data transmission on the switched path; The external Bluetooth array in the non-target area switches to the sleep mode.

7. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 1, characterized in that: The beam width θ of the narrow beam mode in step S4 is negatively correlated with the user density ρ, specifically satisfying: If the environmental interference intensity exceeds -80dBm, on this basis, reduce θ by 10%, and the final beam width θ is not less than 10°; The user density ρ is calculated by the ratio of the number of UWB tags to the sound field partition area.

8. The wireless speaker group cooperative control method based on an external Bluetooth transmitting and receiving array according to claim 1, wherein: The specific implementation of the multi-user priority arbitration mechanism in step S4 includes: Receiving instruction requests from multiple control terminals, and extracting the user role tags (administrator / ordinary user), operation types (emergency mute / volume adjustment), and operation timestamps of the instruction sources; Calculating the instruction priority score according to preset rules: If there are conflicting instructions with a score difference less than 0.1 within the same group, a negotiation confirmation interface is pushed to the user with the lower score.

9. The wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array according to claim 1, wherein: The classification of the high-priority instructions and the low-priority instructions in step S4 includes: High-priority instructions: sound field switching instructions, emergency mute instructions, cross-brand device access requests, system fault warning instructions; Low-priority instructions: volume adjustment instructions (step size ≤ 5%), device status query instructions, ambient light sensing synchronization instructions; The high-priority instructions are directly sent down through the edge gateway, and the response delay ≤ 100 ms; the low-priority instructions are stored in the circular buffer and processed in batches according to a 20-ms time slice.

10. A wireless speaker group collaborative control system based on an external Bluetooth transmitting and receiving array, characterized in that: Using the wireless speaker group collaborative control method based on an external Bluetooth transmitting and receiving array as described in any one of claims 1 to 9, includes: A data acquisition module, integrating a UWB positioning base station, a Bluetooth RSSI acquisition unit, and a spectrum scanning sensor, for obtaining user dynamic position data, system load data, and environmental interference data; A data processing module: for performing dynamic sound field partition calculation, environmental interference assessment, and multi-user arbitration logic; A control execution module: supporting directional beamforming, private channel switching, and cross-brand device protocol conversion; A relay routing management unit, for automatically switching to a standby node when the signal path is interrupted; A virtual device interface pool, storing instruction mapping rules for speakers of different brands, and supporting plug-and-play access Wherein, the external Bluetooth array includes multiple Bluetooth modules supporting beam steering, and the operating frequency band covers the 2.402 GHz - 2.480 GHz standard channels and the 2.412 GHz ± 1 MHz anti-interference private channels.

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