Bandwidth selection method, system, device and medium based on home intelligent terminal

Abstract

The application discloses a bandwidth selection method, system, device and medium based on a household intelligent terminal, relates to the technical field of data processing, and comprises the following steps: acquiring a household bandwidth use device set comprising a plurality of household intelligent terminals, acquiring a new terminal to be added to the household bandwidth use device set, and acquiring a unit time period; respectively acquiring the transmission data amount of the household intelligent terminal in a plurality of continuous unit time periods, eliminating the transmission data amount less than a preset standby data amount, sequentially arranging the plurality of transmission data amounts after elimination to form a data sequence, and acquiring a prediction index according to the data sequence; acquiring the predicted bandwidth of each household intelligent terminal according to the prediction index of each household intelligent terminal; acquiring the target bandwidth of the new terminal according to the total available bandwidth and the predicted bandwidth of each household intelligent terminal, and matching the new terminal with the target bandwidth. The application has the advantages of low multi-device delay, reliable and accurate access bandwidth selection and bandwidth selection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, in particular to a bandwidth selection method, system, device and medium based on a household intelligent terminal. BACKGROUND

[0002] In the current home network environment, with the explosive growth of intelligent terminals (such as wireless microphones, multi-room sound systems, karaoke devices, and audio projectors), dynamic bandwidth selection has many problems.

[0003] First, the existing dynamic bandwidth selection uses fixed bandwidth selection or simple historical mean prediction, which cannot adapt to the intermittent burst working characteristics between home devices. For example: the microphone bursts high traffic when singing, and is almost on standby during the silent period; when multiple devices are activated at the same time (such as home theater mode), new terminals (such as guitar collectors) will occupy the bandwidth of existing devices, causing singing lag, out-of-sync of musical instrument sound and picture, and other experience degradation.

[0004] Second, the existing technology ignores the invalid occupation of bandwidth during the non-active period of the device. Long standby devices (such as idle sound systems) continuously occupy the basic bandwidth, and the actual utilization rate is less than 10%. When a new terminal requests access, the system is forced to compress the resources of real-time streaming devices (such as the main singing microphone) due to the inability to recover idle bandwidth, causing the delay to rise above 200ms, and destroying the real-time nature of singing.

[0005] Finally, the burst traffic prediction mechanism is missing. The existing method uses global historical mean prediction, which does not distinguish between device active / silent periods and underestimates burst demand by more than 40%. The same bandwidth selection strategy is used for high real-time devices (singing microphones) and low-priority devices (light remote controllers), resulting in insufficient key business protection. SUMMARY

[0006] To solve the technical problem of how to simultaneously achieve accurate release of standby device redundant bandwidth, early prediction of burst traffic and reservation of resources, and dynamic allocation of low-delay bandwidth for new terminals under limited total available bandwidth, the present application provides a bandwidth selection method, system, device and medium based on a household intelligent terminal.

[0007] A bandwidth selection method based on home smart terminals includes: acquiring a set of home bandwidth-using devices comprising multiple home smart terminals, acquiring a new terminal to be added to the set of home bandwidth-using devices, and acquiring a unit time period; acquiring the amount of data transmitted by the home smart terminals in multiple consecutive unit time periods, removing data transmission amounts less than a preset standby data amount, and arranging the multiple data transmission amounts after removal into a data sequence, and acquiring a prediction index based on the data sequence; acquiring the predicted bandwidth of each home smart terminal based on the prediction index of each home smart terminal; acquiring the target bandwidth of the new terminal based on the total available bandwidth and the predicted bandwidth of each home smart terminal, and matching the new terminal with the target bandwidth.

[0008] Optionally, obtaining the prediction index based on the data sequence includes: obtaining the difference between the amount of data transmitted in the next transmission and the amount of data transmitted in the previous transmission based on the data sequence, and obtaining the adjustment ratio based on all the differences in the data sequence; obtaining the mean of the amount of data transmitted in the data sequence, and obtaining the prediction index based on the adjustment ratio and the mean.

[0009] Optionally, the adjustment ratio can be obtained from all differences in the data sequence, expressed as: ;in, The adjustment ratio for the data sequence of the j-th home smart terminal. To correct the base, Let J represent the amount of data transmitted in the data sequence of the j-th home smart terminal. For the (i+1)th data item transmitted in the data sequence of the j-th home smart terminal, Let be the amount of data transmitted in the data sequence of the j-th home smart terminal.

[0010] Optionally, obtaining the predicted bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal includes: obtaining the basic bandwidth and obtaining the unit bandwidth corresponding to the unit data volume; obtaining the usage bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal and the unit bandwidth corresponding to the unit data volume; and obtaining the predicted bandwidth of each home smart terminal based on the basic bandwidth and the usage bandwidth of each home smart terminal.

[0011] Optionally, obtaining the target bandwidth of the new terminal based on the total available bandwidth and the predicted bandwidth of each home smart terminal includes: obtaining the total selected bandwidth based on the predicted bandwidth of each home smart terminal; obtaining the bandwidth to be selected based on the total available bandwidth and the total selected bandwidth, and using the bandwidth to be selected as the target bandwidth of the new terminal.

[0012] A bandwidth selection system based on home smart terminals is also provided. The system includes: an acquisition module, used to acquire a set of home bandwidth-using devices including multiple home smart terminals, acquire new terminals to be added to the set of home bandwidth-using devices, and acquire unit time periods; a first data processing module, used to acquire the amount of data transmitted by the home smart terminals in multiple consecutive unit time periods, remove the amount of data transmitted that is less than a preset standby data amount, and arrange the multiple data transmitted after removal into a data sequence, and acquire a prediction index based on the data sequence; a second data processing module, used to acquire the predicted bandwidth of each home smart terminal based on the prediction index of each home smart terminal; and a bandwidth selection module, used to acquire the target bandwidth of the new terminal based on the total available bandwidth and the predicted bandwidth of each home smart terminal, and match the new terminal with the target bandwidth.

[0013] Optionally, the first data processing module is further configured to: obtain the difference between the amount of data transmitted in the next transmission and the amount of data transmitted in the previous transmission based on the data sequence, and obtain the adjustment ratio based on all the differences in the data sequence; obtain the mean value of the amount of data transmitted in the data sequence, and obtain the prediction index based on the adjustment ratio and the mean value.

[0014] Optionally, the second data processing module is further configured to: obtain the basic bandwidth and obtain the unit bandwidth corresponding to the unit data volume; obtain the usage bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal and the unit bandwidth corresponding to the unit data volume; and obtain the predicted bandwidth of each home smart terminal based on the basic bandwidth and the usage bandwidth of each home smart terminal.

[0015] An electronic device is also provided, comprising: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement the bandwidth selection method based on the above-described home smart terminal.

[0016] A non-transitory computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the above-described bandwidth selection method based on a home smart terminal.

[0017] The beneficial effects of this invention are reflected in:

[0018] The bandwidth selection method based on home smart terminals firstly employs a dynamic prediction mechanism based on scenario-based time slicing and data sequence denoising. This completely solves the problem of poor adaptability of existing technologies to the intermittent burst characteristics of devices. By eliminating standby traffic, sensing data change trends, and superimposing adjustments to correct historical averages, the accuracy of predicting burst traffic from devices such as wireless microphones is improved, thus avoiding stuttering and audio-visual tearing caused by underestimating demand to a certain extent. Furthermore, the dual-channel "basic guarantee layer + dynamic demand layer" for predicted bandwidth reserves the minimum basic bandwidth only for silent devices and forces the bandwidth usage to zero, achieving a precise recovery rate of redundant bandwidth from idle devices such as speakers. This significantly improves resource utilization efficiency compared to existing fixed allocation schemes. Finally, a global bandwidth resource pool and a dynamic calculation mechanism for the bandwidth to be selected are established to ensure that the bandwidth required by newly added terminals (such as guitar collectors) comes entirely from the recovered idle resource pool (such as the total redundant bandwidth released by multiple silent devices). This completely avoids resource compression for high real-time services on the existing network (such as lead vocal microphones), ensuring that the latency of existing devices is stably controlled within a low value and the latency of newly added devices is below the standard. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0020] Figure 1 This is a partial flowchart illustrating the bandwidth selection method based on a home smart terminal according to the present invention.

[0021] Figure 2 This is a schematic diagram of another part of the bandwidth selection method based on a home smart terminal of the present invention;

[0022] Figure 3 This is a schematic diagram of another part of the bandwidth selection method based on a home smart terminal of the present invention;

[0023] Figure 4 This is a schematic diagram of another part of the bandwidth selection method based on a home smart terminal of the present invention;

[0024] Figure 5 This is a schematic diagram illustrating the steps of the bandwidth selection method based on a home smart terminal according to the present invention;

[0025] Figure 6 This is a schematic diagram of a portion of step S2 in the bandwidth selection method based on a home smart terminal of the present invention;

[0026] Figure 7This is a schematic diagram of a portion of step S3 in the bandwidth selection method based on a home smart terminal of the present invention;

[0027] Figure 8 This is a schematic diagram of a portion of step S4 in the bandwidth selection method based on a home smart terminal of the present invention;

[0028] Figure 9 This is a block diagram illustrating an electronic device according to an embodiment of the present invention.

[0029] Figure label:

[0030] 700 - Electronic device; 701 - Processor; 702 - Memory; 703 - Multimedia component; 704 - I / O interface; 705 - Communication component. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0032] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0033] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0034] like Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 As shown, a bandwidth selection method based on a home smart terminal is provided, including:

[0035] S1. Obtain a set of home bandwidth usage devices including multiple home smart terminals, obtain new terminals to be added to the set of home bandwidth usage devices, and obtain a unit time period.

[0036] S2. Obtain the amount of data transmitted by the home smart terminal in multiple consecutive time periods, remove the amount of data transmitted that is less than the preset standby data amount, arrange the multiple data transmitted after removal in sequence to form a data sequence, and obtain the prediction index based on the data sequence.

[0037] S3. Obtain the predicted bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal.

[0038] S4. Obtain the target bandwidth of the new terminal based on the total available bandwidth and the predicted bandwidth of each home smart terminal, and match the new terminal with the target bandwidth.

[0039] In this embodiment, it should be noted that in S1, a real-time dynamically updated panoramic view of home network devices is constructed. First, it is necessary to actively detect and accurately identify all smart terminal devices currently connected to the network (e.g., a wireless microphone in the living room, a high-fidelity speaker in the study, a karaoke reverb unit in the basement, background music speakers on the ceiling, etc.), and include them in the "home bandwidth-using device set." This set is a continuously monitored device status database capable of capturing access signals of "new terminals to be added" (e.g., a user starting a new guitar effects collector, its DHCP request, or a specific service discovery broadcast). This access may be actively triggered by the user or intelligently woken up by the device based on the scenario; it must be immediately identified as a new entity to be processed. This step lays the foundation for accurate environmental and status awareness for subsequent dynamic resource scheduling.

[0040] Furthermore, the setting of the unit time period is a window mechanism that adjusts according to the real-time activity scenarios in the home and the communication characteristics of the devices. Based on historical data pattern recognition, the length of this time window is dynamically set by the user's preset settings (such as "running mode" and "silent mode"). For example, when the user initiates an "immersive concert" scenario, or is currently engaged in a home karaoke activity (by determining whether most smart terminal devices are in data transmission mode), the unit time period is set to a shorter preset time period (e.g., 1000ms-5000ms) to accurately capture instantaneous data bursts such as vocal fluctuations and instrument strumming. Conversely, when only background music speakers are detected in a "reading mode" with a stable playlist, the unit time period is changed to a longer preset time period (minutes) to accommodate the smooth and continuous data flow requirements. This adaptive time slicing mechanism based on scenario and traffic patterns flexibly balances the instantaneous response requirements of high-real-time devices (avoiding the masking of sudden events by excessively large windows) with the long-term statistical accuracy of constantly running devices (avoiding redundant fluctuations introduced by excessively small windows), providing a structured temporal foundation for the accuracy of subsequent prediction models.

[0041] In S2, invalid data transmissions from devices are precisely filtered out to establish high-quality input for subsequent predictions. First, for each home smart terminal (such as a wireless microphone), the actual amount of data transmitted over multiple consecutive time periods is captured. To avoid "false occupancy" in standby mode (such as the periodic 10kB heartbeat packets sent by a sleep speaker), a preset standby data volume threshold is set—only valid transmission data exceeding this threshold is retained (e.g., retaining a sudden 50kB acoustic data burst during microphone performance), while all trace data transmissions below the threshold are completely discarded (e.g., discarding only 5kB of total standby traffic over 10 sleep cycles).

[0042] It's important to note that the elimination mechanism is highly fault-tolerant: if a device operates intermittently within a continuous time period (e.g., a karaoke device transmits lyrics data only in 3 out of 5 time units), these discontinuous but valid data points will still be retained (forming a sequence containing 3 data points), rather than being mistakenly judged as completely idle due to periods of inactivity. Conversely, if a device has no valid transmission throughout (e.g., an idle projector remains unactivated), its entire data sequence will be cleared, fundamentally releasing the device's ineffective bandwidth usage. This design avoids the resource waste caused by long-term occupation by silent devices in existing solutions, while also building a data foundation based on the actual needs of active devices.

[0043] Furthermore, after generating the denoised data sequence, a predictive index is produced. First, the difference in variation between adjacent data points in the sequence is calculated (e.g., the fluctuation in data volume from microphone time 1 to time 2), and the overall direction of change is analyzed. If the sum of the differences shows a continuous upward trend (e.g., the data from the instrument acquisition unit increases stepwise due to improvisation), the predicted value is adjusted upwards proportionally; if it shows a downward trend (e.g., microphone data drops sharply at the end of the song), it is adjusted downwards accordingly. This mechanism, by dynamically sensing the device's working state transition (silent → active, active → decay), is significantly different from the rigid historical mean method.

[0044] Furthermore, mean correction and predictive metric synthesis are performed. Based on trend capture, the arithmetic mean of the sequence (representing historical average load) and the aforementioned dynamic adjustment factor are combined to generate the final predictive metric. For example, when the data volume of a certain audio device continuously increases in "home theater" mode, a positive correction value is superimposed on the mean to make the predicted value close to the actual burst demand; while for background music devices with stable data (such as a piano accompaniment stream with constant transmission), the mean is directly used as the predicted value. This dual-track algorithm ensures that the predicted metric conforms to the basic transmission rules of the device (mean protection) and remains sensitive to sudden changes in traffic (trend correction), so that the peak demand of high-priority devices (such as singing microphones) is not underestimated. The predicted metric of standby devices (such as idle audio devices) is 0, and their bandwidth is automatically reclaimed; the predicted metric of intermittently working devices strictly depends on their actual data during active periods; continuously active devices obtain a dynamic predicted value with trend calibration. The three work together to lay the foundation for S3's accurate bandwidth allocation.

[0045] In S3, a predictive bandwidth is used to balance the ability of existing devices to be woken up at any time with real-time traffic demands. First, a basic bandwidth is preset for each smart terminal (such as a 10kbps channel for maintaining connection when a wireless microphone is in standby mode). This value is independent of the actual data traffic and essentially guarantees the minimum physical layer resources (similar to signaling channels in the communications field) to ensure that the device is "always ready to be activated". For example, when the background speaker is in deep sleep, its basic bandwidth is still reserved to ensure that the user can wake up the device within 300ms after pressing the play button, avoiding the several-second delay caused by device reconnection in existing solutions.

[0046] Simultaneously, the dynamic prediction metrics generated by S2 (essentially the corrected predicted data volume) are converted into physical bandwidth resources. First, all devices are allocated a fixed 1Mbps base bandwidth (non-recoverable) to maintain a minimal online state (e.g., the Bluetooth signaling channel of a sleeping microphone), ensuring they can be woken up at any time with a response latency of <300ms. Second, by using a conversion factor that standardizes the unit bandwidth definition for a unit of data volume (e.g., 1kb of data volume maps to 0.01M bandwidth), the prediction metrics are directly mapped to the bandwidth required by the device's services. In short, the conversion can be expressed as: Used bandwidth = Predicted metric × 0.01. Example: A microphone's predicted metric (predicted data volume for the next period) is 800kb → Used bandwidth = 800 × 0.01 = 8M. Finally, the predicted bandwidth is composed of the base bandwidth and the used bandwidth: Predicted bandwidth = 1M (base) + Used bandwidth.

[0047] Furthermore, since the predicted index has been embedded with the device traffic trend through the adjustment ratio in S2, when the device's data transmission volume shows an upward trend (such as during the opening stage of a performance), the adjustment ratio D_j > 1, making the predicted index > historical average → increasing the bandwidth used (e.g., average 500kb × D_j = 1.2 → predicted index 600kb → bandwidth used 6M); when the device's data transmission volume shows a decreasing trend, the adjustment ratio D_j < 1, making the predicted index < average (e.g., average 800kb × D_j = 0.7 → predicted index 560kb → bandwidth used 5.6M). In summary, the system achieves zero occupancy of silent devices, with an idle audio prediction index of 0, resulting in a predicted bandwidth of 1M (base bandwidth). It also ensures high protection for sudden device interruptions, with the karaoke host receiving 1.3M of bandwidth usage due to its increasing trend, leading to a total predicted bandwidth of 2.3M (base 1M + usage 1.3M). When a guitar collector requests access, it reclaims redundant bandwidth from idle devices (e.g., previously occupying 5M, now only requiring 1M), dynamically allocating all redundant bandwidth (4M) to new devices to ensure low-latency operation.

[0048] In S4, the predicted bandwidth of all active devices is first aggregated. The predicted bandwidth (including base bandwidth + used bandwidth) of each terminal in the home bandwidth-using device set is iterated through, and the total selected bandwidth is obtained by summing the data. For example, the predicted bandwidth of a singing microphone = base bandwidth + used bandwidth (dynamically adjusted value), the predicted bandwidth of a speaker = base bandwidth (used bandwidth is zero in silent state), and the predicted bandwidth of other silent devices is compressed to only the base bandwidth. The predicted bandwidths of all devices are added together to obtain the total predicted bandwidth (i.e., the total selected bandwidth). Then, the difference between the total predicted bandwidth and the total available bandwidth is calculated in real time to determine the bandwidth pool to be selected (forming the subsequent target bandwidth). This step essentially constructs a resource buffer based on real demand, which is fundamentally different from existing solutions where insufficient selectable bandwidth is caused by the failure to reclaim idle bandwidth.

[0049] Furthermore, a lossless bandwidth allocation strategy is implemented for new terminals. The entire bandwidth pool to be selected (i.e., the total redundancy released by all devices, which is the target bandwidth) is allocated to the new terminal as the target bandwidth. For example, when adding a guitar collector: it directly inherits the 4M redundant bandwidth released by the idle speaker, and adds the 2M redundant bandwidth recycled from the standby light; therefore, the target bandwidth can be expressed as target bandwidth = total available bandwidth - total selected bandwidth.

[0050] In summary, the bandwidth selection method based on home smart terminals firstly employs a dynamic prediction mechanism based on scenario-based time slicing and data sequence denoising. This completely solves the problem of poor adaptability of existing technologies to the intermittent burst characteristics of devices. By eliminating standby traffic, sensing data change trends, and superimposing adjustments to correct historical averages, the accuracy of predicting burst traffic from devices such as wireless microphones is improved, thus avoiding stuttering and audio-visual tearing caused by underestimating demand to a certain extent. Furthermore, the dual-channel "basic guarantee layer + dynamic demand layer" for predicted bandwidth reserves the minimum basic bandwidth only for silent devices and forces the bandwidth usage to zero, achieving a precise recovery rate of redundant bandwidth from idle devices such as speakers, significantly improving resource utilization efficiency compared to existing fixed allocation schemes. Finally, a global bandwidth resource pool and a dynamic calculation mechanism for the bandwidth to be selected are established to ensure that the bandwidth required by newly added terminals (such as guitar collectors) comes entirely from the recovered idle resource pool (such as the total redundant bandwidth released by multiple silent devices), completely avoiding resource compression for high real-time services on the existing network (such as lead vocal microphones), ensuring that the latency of existing devices is stably controlled within a low value and the latency of newly added devices is below the standard. In summary, this end-to-end optimization enables the system to maintain a stable experience without lag or synchronization distortion for critical business operations even in high-concurrency scenarios with multiple devices (such as running multiple devices simultaneously in home music entertainment mode and being able to add multiple terminals).

[0051] like Figure 6 As shown, in one embodiment, obtaining the prediction index based on the data sequence in S2 includes:

[0052] S21. Obtain the difference between the amount of data transmitted in the next transmission and the amount of data transmitted in the previous transmission based on the data sequence, and obtain the adjustment ratio based on all the differences in the data sequence;

[0053] S22. Obtain the mean value of the amount of data transmitted in the data sequence, and obtain the prediction index based on the adjustment ratio and the mean value.

[0054] In this embodiment, it should be noted that in S21, the state transition of device bandwidth usage behavior is captured by analyzing the difference between consecutive adjacent data. First, for each device's data sequence (e.g., 15 transmission records of a wireless microphone), the continuous change in data volume between adjacent time periods is calculated (i.e., the amount of data transmitted in the later time period minus the amount of data transmitted in the previous time period). For example: if the sequence rises in a stepwise manner from low to medium to high (e.g., the crescendo phase of background music), the difference is a continuous positive value; if the sequence falls in a stepwise manner from high to medium to low (e.g., the phase of vocals fading out), the difference is a continuous negative value; if the sequence fluctuates drastically (e.g., low to high to low in an improvisation), the difference alternates between positive and negative. Then, the overall trend direction is determined, and all continuous changes are summed algebraically. The sign of the sum indicates a significant increase in device transmission status; a positive sum indicates that the device has entered an active ramp-up phase; a negative sum indicates that the device has entered a silent decay phase; stable demand: the sum approaches zero, indicating that the device is in a steady-state transmission phase.

[0055] In summary, by analyzing the persistence (not the amplitude) of the change, the existing scheme avoids misjudging occasional fluctuations. For example, a single sudden increase in data during the interlude of a karaoke device will not be misidentified as a long-term upward trend.

[0056] In S22, historical averages are linked to dynamic trends. The arithmetic mean of the data series is calculated, reflecting the basic load level of the equipment within the statistical period. The mean weight is dynamically adjusted based on the trend direction output from S21 and the built-in correction parameters.

[0057] When the equipment is in an increasing state (total > 0), the average value is increased proportionally (e.g., average 500kb × adjustment ratio 1.2 → predicted target 600kb) to reserve a margin for potential surges. When the equipment is in a decreasing state (total < 0), the average value is decreased proportionally (e.g., average 800kb × adjustment ratio 0.7 → predicted target 560kb) to avoid resource redundancy. When the equipment trend is not significant, the adjustment ratio ≈ 1, and the predicted target ≈ the average value.

[0058] Home theater startup phase: Projector data sequence difference sum +38 (strong upward trend) → Adjustment ratio 1.3 → Predictive index = historical average × 1.3, covering the upcoming 4K video stream burst. Concert end buffer period: Microphone difference sum -15 (strong downward trend) → Adjustment ratio 0.6 → Predictive index = historical average × 0.6, quickly releasing redundant bandwidth to the resource pool.

[0059] It should also be noted that the adjustment ratio obtained from all differences in the data sequence in S21 is expressed as follows: ;in, The adjustment ratio for the data sequence of the j-th home smart terminal. To correct the base, Let J represent the amount of data transmitted in the data sequence of the j-th home smart terminal. For the (i+1)th data item transmitted in the data sequence of the j-th home smart terminal, Let be the amount of data transmitted in the data sequence of the j-th home smart terminal.

[0060] It should also be noted that in the entire expression, firstly, the trend direction of the algebraic sum of differences is extracted. Then, the difference in the amount of adjacent transmitted data within a continuous unit time period is calculated. For example, microphones during silence Entering a peak period for singing The difference is positive; for example, the data volume drops sharply at the end of the song. . Summing all continuous differences essentially calculates the net direction of change of the device within the entire observation window. A positive sum indicates that the device is in a continuous active state (such as a microphone continuously rising for multiple periods during a performance), a negative sum indicates that the device is in a continuous silent decay state (such as the device going to sleep after a home theater session ends), and a sum approaching zero indicates that the device is in a steady-state transmission state (such as background music). In short, algebraic sums avoid the shortcomings of existing schemes that misjudge occasional surges (such as a single strum of a musical instrument) as long-term trends by capturing the continuous direction of change in flow (not single-point fluctuations).

[0061] Furthermore, the sign function The algebraic sum is mapped to -1, 0, or 1; algebraic sum > 0 → 1, algebraic sum < 0 → -1, algebraic sum = 0 → 0. This suppresses amplitude interference, ignores the absolute value of flow changes (e.g., a sudden increase of 10kB or 100kB is considered the same upward trend), and avoids amplifying single device jitters (such as instantaneous commands from a light remote control) into false trends. Furthermore, it strengthens state transitions, retaining only three state labels: "rising / falling / stable," allowing predictions to focus on the essential working stage transitions. It also filters out instantaneous interference from low-priority devices (such as micro-flow fluctuations in a light remote control) to prevent them from crowding out prediction resources from high-real-time devices (microphones).

[0062] Furthermore, As a preset correction base, it controls the intensity of the adjustment ratio's response to the trend. This is used in high real-time scenarios (such as concert mode). →Activate device adjustment ratio up to 1.3; low-sensitivity scenarios (such as reading mode) are set... →Avoid over-response of steady-state devices. Adjust proportional synthesis. When increasing (like → ); When decreasing (like → ); when stable Therefore, the upper limit of the predicted value is automatically increased for increasing devices to eliminate the risk of underestimation by the historical average method; the predicted value is reduced proportionally for decreasing devices to achieve rapid recovery of idle bandwidth.

[0063] like Figure 7 As shown, in one embodiment, obtaining the predicted bandwidth of each home smart terminal based on the predicted metrics of each home smart terminal in S3 includes:

[0064] S31. Obtain the basic bandwidth and the unit bandwidth corresponding to the unit data volume;

[0065] S32. Obtain the bandwidth used by each home smart terminal based on the predicted indicators and the unit bandwidth corresponding to the unit data volume of each home smart terminal.

[0066] S33. Obtain the predicted bandwidth of each home smart terminal based on the basic bandwidth and the bandwidth used by each home smart terminal.

[0067] In this embodiment, it should be noted that in S31, firstly, a basic bandwidth is set. This bandwidth is fixed and is the minimum resource reserved for all devices (e.g., 1Mbps reserved for each smart terminal), regardless of whether the device is currently active or in standby mode. Its core function is to maintain the minimum online connectivity of the devices, ensuring that the devices can be woken up instantly even in deep sleep mode (e.g., background audio responds within 300ms after the user presses the play button), completely avoiding the high latency problem in traditional solutions where devices need to re-handshake due to disconnection. Secondly, the unit bandwidth conversion rule corresponding to the unit data volume is clearly defined (e.g., it is agreed that 0.01M physical bandwidth is required for every 1kb of data transmission). This rule provides a universal and quantifiable conversion standard for accurately converting the predicted data traffic demand into the actual physical bandwidth demand, which is the basis for dynamic resource modeling.

[0068] In S32, the predicted metrics (representing future data volume requirements) generated in S2, which already contain the real-time status trend of the device (reflected through adjustment ratios), are precisely converted into the dynamic bandwidth required for the device's business operation, according to the conversion rules established in S31. The conversion logic is expressed as: Bandwidth Used = Predicted Metric × Unit Bandwidth. For example, a wireless microphone in its active growth phase might have its predicted metrics adjusted to a level higher than its historical average due to its continuous upward trend (e.g., average 500kb × adjustment ratio 1.2 = 600kb). Multiplying this by the unit bandwidth coefficient (0.01) yields a dynamic bandwidth of 6M. Conversely, a completely silent projector has a predicted metric of 0. Regardless of the unit bandwidth corresponding to its base bandwidth, its calculated bandwidth usage will inevitably be 0M, meaning it does not occupy the dynamic resource layer required for business data.

[0069] In S33, the final predicted bandwidth is synthesized based on the characteristics and status of each device: the fixed resources (basic bandwidth) set in S31 are superimposed and combined with the dynamic demand (usage bandwidth) calculated in S32 to form the predicted bandwidth = basic bandwidth + usage bandwidth. This synthesis mechanism features intelligent resource isolation: for devices that are in standby mode (such as idle speakers), their bandwidth usage is 0, so the predicted bandwidth is equal to the base bandwidth (occupying only 1Mbps), which releases a large amount of redundant resources compared to traditional fixed allocation schemes; for devices in burst transmission mode (such as projectors in home theaters), their predicted bandwidth is equal to the base bandwidth plus their highly dynamic usage bandwidth (such as 1M + 20M). The two parts of resources are logically isolated, with the base part ensuring the absolute priority of control signaling and the usage part carrying core business data streams; more importantly, this structure ensures that when bandwidth selection is needed for new devices (such as newly added guitar collectors), the required bandwidth comes entirely from the redundant bandwidth recovered from silent devices (such as the 4M saved from idle speakers), without compressing the base bandwidth or allocated usage bandwidth of existing active devices, thus solving the technical problem of high latency caused by new devices accessing and occupying critical resources (such as lead vocal microphones).

[0070] like Figure 8 As shown, in one embodiment, obtaining the target bandwidth of the new terminal in S4 based on the total available bandwidth and the predicted bandwidth of each home smart terminal includes:

[0071] S41. Obtain the total selected bandwidth based on the predicted bandwidth of each home smart terminal;

[0072] S42. Obtain the bandwidth to be selected based on the total available bandwidth and the total selected bandwidth, and use the bandwidth to be selected as the target bandwidth of the new terminal.

[0073] In this embodiment, it should be noted that in S41, all devices (including active and silent devices) are traversed, and all predicted bandwidths are accumulated to obtain the total selected bandwidth. Example: In home theater mode, the system accumulates the predicted bandwidths of all home smart terminals such as projectors, speakers, and microphones.

[0074] In S42, lossless access to new terminals is achieved through bandwidth resource isolation and reallocation: the total available bandwidth is subtracted from the total selected bandwidth to generate a pool of bandwidth to be selected. This pool is essentially the total amount of redundancy released by all devices and is completely isolated from the resources of active devices on the existing network. The entire bandwidth pool is allocated to new terminals as the target bandwidth. For example, when adding a guitar capture device, its required bandwidth comes entirely from the resources within the pool, rather than compressing the 8M dynamic bandwidth of the singing microphone.

[0075] A bandwidth selection system based on a home smart terminal is also provided, the system comprising:

[0076] The acquisition module is used to acquire a set of home bandwidth-using devices including multiple home smart terminals, acquire new terminals to be added to the set of home bandwidth-using devices, and acquire a unit time period.

[0077] The first data processing module is used to obtain the amount of data transmitted by the home smart terminal in multiple consecutive unit time periods, remove the amount of data transmitted that is less than the preset standby data amount, arrange the multiple data transmitted after removal in sequence to form a data sequence, and obtain the prediction index based on the data sequence.

[0078] The second data processing module is used to obtain the predicted bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal.

[0079] The bandwidth selection module is used to obtain the target bandwidth of the new terminal based on the total available bandwidth and the predicted bandwidth of each home smart terminal, and to match the new terminal with the target bandwidth.

[0080] In one embodiment, the first data processing module is further configured to: obtain the difference between the amount of data transmitted in the next transmission and the amount of data transmitted in the previous transmission based on the data sequence, and obtain an adjustment ratio based on all the differences in the data sequence; obtain the mean value of the amount of data transmitted in the data sequence, and obtain a prediction index based on the adjustment ratio and the mean value.

[0081] In one embodiment, the second data processing module is further configured to: obtain the basic bandwidth (the bandwidth allocated to each home smart terminal when it is in standby mode, ensuring that each home smart terminal can be used at any time), and obtain the unit bandwidth corresponding to the unit data volume; obtain the usage bandwidth of each home smart terminal based on the predicted indicators of each home smart terminal and the unit bandwidth corresponding to the unit data volume; and obtain the predicted bandwidth of each home smart terminal based on the basic bandwidth and the usage bandwidth of each home smart terminal.

[0082] In this embodiment, it should be noted that the specific method of performing the operation of the bandwidth selection system based on home smart terminals has been described in detail in the embodiments of the bandwidth selection method based on home smart terminals, and will not be elaborated here.

[0083] Figure 9 This is a block diagram of an electronic device according to an exemplary embodiment, illustrating a bandwidth selection method based on a home smart terminal. Figure 9 As shown, the electronic device 700 may include: a processor 701 and a memory 702. The electronic device 700 may also include one or more of a multimedia component 703, an I / O interface 704 (input / output interface), and a communication component 705.

[0084] The processor 701 controls the overall operation of the electronic device 700 to complete all or part of the steps in the bandwidth selection method based on the home smart terminal described above. The memory 702 stores various types of data to support the operation of the electronic device 700. This data may include, for example, instructions for any application or method operating on the electronic device 700, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 703 may include a screen and audio components. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 702 or transmitted via communication component 705. The audio component also includes at least one speaker for outputting audio signals. I / O interface 704 provides an interface between processor 701 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IoT, eMTC, or other 5G technologies, or a combination thereof, is not limited here. Therefore, the corresponding communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0085] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the bandwidth selection method based on the home smart terminal described above.

[0086] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the bandwidth selection method based on a home smart terminal described above. For example, the computer-readable storage medium may be the memory 702 including program instructions described above, which may be executed by the processor 701 of the electronic device 700 to complete the bandwidth selection method based on a home smart terminal described above.

[0087] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described bandwidth selection method based on a home smart terminal when executed by the programmable device.

[0088] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0089] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0090] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A bandwidth selection method based on a home intelligent terminal, characterized in that, The method comprises the following steps: acquiring a home bandwidth usage device set comprising a plurality of home intelligent terminals, acquiring a new terminal to be added to the home bandwidth usage device set, and acquiring a unit time period; respectively acquiring transmission data amounts of the home intelligent terminals in a plurality of continuous unit time periods, eliminating transmission data amounts less than a preset standby data amount, and sequentially arranging the plurality of transmission data amounts after elimination to form a data sequence; acquiring a difference between a next transmission data amount and a previous transmission data amount according to the data sequence, and acquiring an adjustment ratio according to all the differences in the data sequence; Wherein, the adjustment ratio is represented as: ; wherein, is the adjustment ratio of the data sequence of the jth household intelligent terminal, is the correction base, is the number of transmission data in the data sequence of the jth household intelligent terminal, is the i+1th transmission data in the data sequence of the jth household intelligent terminal, is the ith transmission data in the data sequence of the jth household intelligent terminal; acquiring a mean value of the transmission data amounts in the data sequence, and acquiring a prediction index according to the adjustment ratio and the mean value; acquiring a basic bandwidth, and acquiring a unit bandwidth corresponding to a unit data amount; acquiring usage bandwidths of the respective home intelligent terminals according to the prediction indexes of the respective home intelligent terminals and the unit bandwidth corresponding to the unit data amount; and acquiring prediction bandwidths of the respective home intelligent terminals according to the basic bandwidth and the usage bandwidths of the respective home intelligent terminals; acquiring a target bandwidth of the new terminal according to a total available bandwidth and the prediction bandwidths of the respective home intelligent terminals, and matching the new terminal with the target bandwidth.

2. The bandwidth selection method based on the home intelligent terminal according to claim 1, characterized in that, The acquiring of the target bandwidth of the new terminal according to the total available bandwidth and the prediction bandwidths of the respective home intelligent terminals comprises: acquiring a total selected bandwidth according to the prediction bandwidths of the respective home intelligent terminals; acquiring a to-be-selected bandwidth according to the total available bandwidth and the total selected bandwidth, and taking the to-be-selected bandwidth as the target bandwidth of the new terminal.

3. A bandwidth selection system based on a home intelligent terminal, characterized by, The system is used to implement the home intelligent terminal-based bandwidth selection method in claim 1 or claim 2, and the system comprises: an acquisition module, configured to acquire a home bandwidth usage device set comprising a plurality of home intelligent terminals, acquire a new terminal to be added to the home bandwidth usage device set, and acquire a unit time period; a first data processing module, configured to respectively acquire transmission data amounts of the home intelligent terminals in a plurality of continuous unit time periods, eliminate transmission data amounts less than a preset standby data amount, sequentially arrange the plurality of transmission data amounts after elimination to form a data sequence, and acquire a prediction index according to the data sequence; a second data processing module, configured to acquire prediction bandwidths of the respective home intelligent terminals according to the prediction indexes of the respective home intelligent terminals; a bandwidth selection module, configured to acquire a target bandwidth of the new terminal according to a total available bandwidth and the prediction bandwidths of the respective home intelligent terminals, and match the new terminal with the target bandwidth.

4. The bandwidth selection system based on a home intelligent terminal according to claim 3, wherein, The first data processing module is further configured to: acquire a difference between a next transmission data amount and a previous transmission data amount according to the data sequence, and acquire an adjustment ratio according to all the differences in the data sequence; acquire a mean value of the transmission data amounts in the data sequence, and acquire a prediction index according to the adjustment ratio and the mean value.

5. The bandwidth selection system based on a home intelligent terminal according to claim 3, wherein, The second data processing module is further configured to: acquire a basic bandwidth, and acquire a unit bandwidth corresponding to a unit data amount; acquire usage bandwidths of the respective home intelligent terminals according to the prediction indexes of the respective home intelligent terminals and the unit bandwidth corresponding to the unit data amount; acquire prediction bandwidths of the respective home intelligent terminals according to the basic bandwidth and the usage bandwidths of the respective home intelligent terminals.

6. An electronic device, comprising: The system is used to implement the home intelligent terminal-based bandwidth selection method in claim 1 or claim 2, and the system comprises: a memory having a computer program stored thereon; A processor for executing the computer program in the memory to implement the home intelligent terminal based bandwidth selection method in claim 1 or claim 2.

7. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the home intelligent terminal based bandwidth selection method in claim 1 or claim 2.

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