Energy distribution method and device for dual-channel wireless equipment, equipment, medium and product

Abstract

The invention relates to an energy distribution method and device for dual-channel wireless equipment, equipment, a medium and a product, and the method comprises the steps: obtaining the current residual energy of a power supply of a target object, the fitting relation between the service time of a main channel and the service frequency, and the online estimation time of a plurality of main channels, and obtaining the online estimation time of a plurality of main channels according to the current residual energy of the power supply; determining available duration of a power supply; according to the fitting relationship, determining the confidence degree corresponding to each main channel online estimated time length, and determining the main channel online estimated time length corresponding to the maximum confidence degree as a target online estimated time length; and comparing the target online estimated duration with the available duration of the power supply to obtain a comparison result, and distributing the residual energy of the power supply according to the comparison result. According to the energy distribution method of the dual-channel wireless equipment, the rationality and reliability during power supply residual energy distribution can be improved, so that the balance between the online duration of the main channel and the user experience can be better realized.

Description

Technical Field

[0001] The present application relates to the technical field of dual-channel wireless devices, and in particular to an energy distribution method, device, equipment, medium and product for dual-channel wireless devices. Background Art

[0002] A dual-channel wireless device is a device with two independent connection channels (two paths). The two channels have a master-slave relationship and can transmit information simultaneously or separately. The master channel is used to implement basic functions, and the slave channel is used to improve user experience. The two channel sub-devices are usually powered by the same power supply. Dual-channel devices have higher performance and can bring better user experience.

[0003] However, under the condition of power energy limitation, there is a contradictory relationship between the online time of the main channel and the user experience. If more energy is used for the slave channel to improve the user experience, the online time of the main channel will be reduced; if more energy is used for the main channel to realize basic functions, the user experience will be reduced. Therefore, an energy allocation method for dual-channel wireless devices is urgently needed to achieve a balance between the online time of the main channel and the user experience. Summary of the invention

[0004] Based on this, it is necessary to provide an energy allocation method, device, computer equipment, computer-readable storage medium and computer program product for a dual-channel wireless device to address the above-mentioned technical problem of how to achieve a balance between the online time of the main channel and the user experience.

[0005] In a first aspect, the present application provides an energy allocation method for a dual-channel wireless device, the method comprising:

[0006] Obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the estimated online time of multiple main channels, and determine the available power time based on the current remaining power;

[0007] According to the fitting relationship, the confidence level corresponding to the online estimated duration of each main channel is determined, and the online estimated duration of the main channel corresponding to the maximum confidence level is determined as the target online estimated duration;

[0008] Compare the target online estimated duration with the available power duration to obtain a comparison result, and allocate the remaining power energy according to the comparison result.

[0009] In one embodiment, a method for determining a fitting relationship between the main channel usage time and the usage frequency includes:

[0010] Obtain historical usage data of the target object, the historical usage data including historical usage duration and its corresponding historical usage frequency;

[0011] According to the preset data fitting strategy, the historical usage data is fitted to obtain the fitting relationship between the usage time and the usage frequency of the main channel.

[0012] In one embodiment, determining the confidence level corresponding to the online estimated duration of each main channel according to the fitting relationship includes:

[0013] Obtaining the usage demand information of the target object, and determining the main channel occupancy weight and the secondary channel occupancy weight according to the usage demand information;

[0014] According to the fitting relationship, the balance coefficient of the online estimated duration of each main channel is determined;

[0015] The confidence level of the online estimated duration of each main channel is determined based on the balance coefficient, the main channel occupancy weight, and the slave channel occupancy weight.

[0016] In one embodiment, allocating the remaining energy of the power supply according to the comparison result includes:

[0017] When the comparison result shows that the target online estimated duration is not greater than the available power duration, the remaining energy of the power supply is distributed to the master channel and the slave channel;

[0018] When the comparison result shows that the target online estimated duration is greater than the power available duration, the remaining energy of the power supply is allocated to the main channel.

[0019] In one embodiment, determining the available power duration according to the current remaining power of the power source includes:

[0020] The current energy consumption rate of the target object is obtained, and the available power supply duration is determined according to the current remaining power of the power supply and the current energy consumption rate.

[0021] In one embodiment, the method further comprises:

[0022] Determine the historical usage duration, historical usage frequency and historical usage pattern of the main channel within a preset historical period based on the historical usage data;

[0023] Obtain the duration prediction model of the target object, input the historical usage duration, historical usage frequency, and historical usage pattern of the main channel into the time series model, and obtain the online estimated duration of multiple main channels.

[0024] In a second aspect, the present application also provides an energy distribution device for a dual-channel wireless device, the device comprising:

[0025] The target object data acquisition module is used to obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determine the available power time according to the current remaining power;

[0026] An online estimated duration determination module is used to determine the confidence corresponding to the online estimated duration of each main channel according to the fitting relationship, and determine the online estimated duration of the main channel corresponding to the maximum confidence as the target online estimated duration;

[0027] The power supply remaining energy allocation module is used to compare the target online estimated duration with the power supply available duration, obtain a comparison result, and allocate the power supply remaining energy according to the comparison result.

[0028] In a third aspect, the present application further provides a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0029] Obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the estimated online time of multiple main channels, and determine the available power time based on the current remaining power;

[0030] According to the fitting relationship, the confidence level corresponding to the online estimated duration of each main channel is determined, and the online estimated duration of the main channel corresponding to the maximum confidence level is determined as the target online estimated duration;

[0031] Compare the target online estimated duration with the available power duration to obtain a comparison result, and allocate the remaining power energy according to the comparison result.

[0032] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0033] Obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the estimated online time of multiple main channels, and determine the available power time based on the current remaining power;

[0034] According to the fitting relationship, the confidence level corresponding to the online estimated duration of each main channel is determined, and the online estimated duration of the main channel corresponding to the maximum confidence level is determined as the target online estimated duration;

[0035] Compare the target online estimated duration with the available power duration to obtain a comparison result, and allocate the remaining power energy according to the comparison result.

[0036] In a fifth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0037] Obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the estimated online time of multiple main channels, and determine the available power time based on the current remaining power;

[0038] According to the fitting relationship, the confidence level corresponding to the online estimated duration of each main channel is determined, and the online estimated duration of the main channel corresponding to the maximum confidence level is determined as the target online estimated duration;

[0039] Compare the target online estimated duration with the available power duration to obtain a comparison result, and allocate the remaining power energy according to the comparison result.

[0040] The energy allocation method, device, computer device, storage medium and computer program product of the dual-channel wireless device mentioned above, when allocating energy to the dual-channel wireless device, first obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determine the available power time according to the current remaining power. Then, according to the fitting relationship, determine the confidence corresponding to the online estimated time of each main channel, and determine the main channel online estimated time corresponding to the maximum confidence as the target online estimated time, so as to obtain a more accurate main channel online estimated time. Finally, compare the target online estimated time with the available power time to obtain a comparison result, and allocate the remaining power energy according to the comparison result to achieve a reasonable allocation of the remaining energy of the power.

[0041] The energy allocation method for a dual-channel wireless device of the present application first determines the available power supply time based on the current remaining energy of the power supply, then determines the confidence corresponding to each main channel online estimated time based on the fitting relationship, and determines the main channel online estimated time corresponding to the maximum confidence as the final main channel online estimated time, which helps to improve the reliability of subsequent comparison results, thereby improving the rationality and reliability of the remaining energy allocation of the power supply, and further helps to achieve a balance between the main channel online time and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] FIG1 is an application environment diagram of an energy distribution method for a dual-channel wireless device in one embodiment;

[0043] FIG2 is a flow chart of a method for allocating energy to a dual-channel wireless device in one embodiment;

[0044] FIG3 is a flow chart of determining a fitting relationship between a main channel usage duration and a usage frequency in one embodiment;

[0045] FIG4 is a flow chart of determining the confidence level of each main channel online estimated duration in one embodiment;

[0046] FIG5 is a flow chart of determining the allocation of remaining power supply energy according to a comparison result in one embodiment;

[0047] FIG6 is a flow chart of determining the estimated online duration of multiple main channels in one embodiment;

[0048] FIG7 is a block diagram of a structure of an energy distribution device for a dual-channel wireless device in one embodiment;

[0049] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] A dual-channel wireless device is a device with two independent connection channels (two paths). The two channels have a master-slave relationship and can transmit information simultaneously or separately. The master channel is used to implement basic functions, and the slave channel is used to improve user experience. The two channel sub-devices are usually powered by the same power supply. Dual-channel devices are usually used in application scenarios that require higher performance or better user experience, such as audio and video transmission. The dual-channel design can improve data transmission efficiency and stability and reduce signal interference and delay.

[0052] However, under the condition of power energy limitation, there is a contradictory relationship between the online time of the main channel and the user experience. If more energy is used for the slave channel to improve the user experience, the online time of the main channel will be reduced; if more energy is used for the main channel to realize basic functions, the user experience will be reduced. Therefore, an energy allocation method for dual-channel wireless devices is urgently needed to achieve a balance between the online time of the main channel and the user experience.

[0053] In response to the above-mentioned technical problem of how to achieve a balance between the online time of the main channel and the user experience, an embodiment of the present application provides an energy distribution method for a dual-channel wireless device, which can be applied to an energy distribution system for a dual-channel wireless device as shown in Figure 1. The system includes a dual-channel wireless device 102 and a control device 104. The dual-channel wireless device 102 is connected to the control device 104 in a wired or wireless manner. The dual-channel wireless device 102 includes but is not limited to dual-channel wireless devices such as audio-channel Bluetooth headsets, smart speakers, and smart sound columns. The control device 104 is used to send control instructions to the dual-channel wireless device 102 to control the operating state or operating mode of the wireless device 102. The control device 104 includes but is not limited to mobile phones, computers, tablet computers, and other electronic devices that can realize data interaction with the dual-channel wireless device 102. The control device 104 can also be directly integrated or loaded on the dual-channel wireless device 102 to form a whole.

[0054] In some embodiments, as shown in FIG2 , the method is applied to a control device as an example for illustration. In this embodiment, the method includes the following steps:

[0055] Step 202, obtaining the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determining the available power time according to the current remaining power.

[0056] The target object can be any wireless device among dual-channel wireless devices, for example, dual-channel Bluetooth headsets, smart speakers, smart sound columns and other dual-channel wireless devices. The fitting relationship between the main channel usage time and the usage frequency is used to characterize the mapping relationship between the main channel usage time and the usage frequency. That is to say, according to a certain estimated main channel usage time, that is, the main channel online estimated time, the corresponding usage frequency can be determined. The usage frequency is used to characterize the frequency of occurrence of a certain main channel usage time, which can be counted based on the historical usage data within a preset historical time period. The main channel online estimated time can be determined based on the usage demand information received by the target object, or it can be determined based on the current usage status of the target object. The available power supply time is used to characterize the remaining time that the remaining energy of the current power supply can be used.

[0057] Specifically, the target object can obtain control instructions from the control device. The control instructions are issued according to the user's usage needs, and the control instructions carry multiple main channel online estimated duration values. Alternatively, based on the user's usage needs, the system can also automatically generate multiple possible main channel online estimated duration values.

[0058] Step 204: Determine the confidence level corresponding to each main channel online estimated duration according to the fitting relationship, and determine the main channel online estimated duration corresponding to the maximum confidence level as the target online estimated duration.

[0059] According to step 202, there are multiple possible values ​​for the estimated online duration of the main channel. In order to determine the value that best meets the current remaining energy situation of the power supply and to meet the requirements of balancing the online duration of the main channel and the user experience, it is necessary to determine the most reliable online estimated duration of the main channel from the multiple estimated online durations of the main channel, that is, the target online estimated duration. The most reliable means the one with the highest confidence. That is to say, the confidence is used to characterize the reliability or desirability of the estimated online duration of the main channel. The greater the confidence of the estimated online duration of the main channel, the more likely it is that the estimated online duration of the main channel will be determined as the target online estimated duration.

[0060] For example, taking the online estimated durations of multiple main channels as 10 minutes, 20 minutes, and 30 minutes, and the corresponding confidence levels as 0.5, 1, and 1.5, respectively, it can be determined that the confidence level corresponding to 30 minutes is the largest, and 30 minutes is determined as the final target online estimated duration of the main channel.

[0061] Step 206 , compare the target online estimated duration with the power available duration to obtain a comparison result, and allocate the remaining power energy according to the comparison result.

[0062] Since the available power supply duration determines the available time of the remaining power supply energy, after obtaining the target online estimated duration, it is necessary to determine the allocation of the remaining power supply energy based on the comparison result between the target online estimated duration and the available power supply duration. The comparison result may be that the target online estimated duration is not greater than the available power supply duration, or that the target online estimated duration is greater than the available power supply duration.

[0063] The energy allocation method for the dual-channel wireless device described above first determines the available power time based on the current remaining energy of the power supply, then determines the confidence corresponding to each main channel online estimated time based on the fitting relationship, and determines the main channel online estimated time corresponding to the maximum confidence as the final main channel online estimated time, which helps to improve the reliability of the subsequent comparison results, thereby improving the rationality and reliability of the remaining energy allocation of the power supply, and further helps to achieve a balance between the main channel online time and user experience.

[0064] In one embodiment, as shown in FIG3 , a method for determining a fitting relationship between the main channel usage time and the usage frequency includes:

[0065] Step 302: Acquire historical usage data of the target object, where the historical usage data includes historical usage duration and its corresponding historical usage frequency.

[0066] When determining the fitting relationship between the usage time and the usage frequency of the main channel of the target object, a large amount of real historical usage data is required to ensure the accuracy and reliability of the final fitting relationship. Specifically, the historical usage data of the target object can be the usage time of the main channel of the target object each time within a preset historical time period (i.e., the historical usage time), the time period of each use, and other historical data, for example, the historical usage time of each use of the current object in the past month and the time period of each use. The usage frequency of the main channel is determined based on the usage time of each time within the preset time period.

[0067] For example, the historical usage duration and its corresponding historical usage frequency obtained according to the historical usage data of the target object in the last seven days are shown in Table 1:

[0068]

[0069] Table 1

[0070] According to Table 1, the historical usage time of the main channel of the target object in the past seven days is 10 minutes, 15 minutes, 20 minutes, 25 minutes, and 30 minutes respectively. Assuming that the total number of times the main channel is used in the past seven days is this, then according to the usage frequency corresponding to 10 minutes is 0.2, it can be known that the target object has used the main channel twice in the past seven days with a usage time of 10 minutes.

[0071] Step 304: Fit the historical usage data according to a preset data fitting strategy to obtain a fitting relationship between the usage time and the usage frequency of the main channel.

[0072] The data fitting strategy preset in this embodiment is to determine the probability density of the random main channel online estimated duration according to a probability distribution function. By fitting the historical usage data of the target object using the probability distribution function, a fitting relationship between the main channel usage duration and usage frequency can be obtained.

[0073] Exemplarily, the probability distribution function is expressed as follows:

[0074] f(x)= ;

[0075] In the formula, It is the average value determined based on the historical usage time of the main channel within the preset historical time. It is the standard deviation determined based on the historical usage duration of the main channel within the preset historical time period.

[0076] In this embodiment, the fitting relationship obtained according to the preset data fitting strategy and a large amount of historical usage data has high accuracy and reliability, so that the corresponding usage frequency can be determined according to the estimated online duration of each main channel.

[0077] In one embodiment, as shown in FIG4 , the confidence level corresponding to the online estimated duration of each main channel is determined according to the fitting relationship, including:

[0078] Step 402: Obtain usage demand information of the target object, and determine the main channel occupancy weight and the secondary channel occupancy weight according to the usage demand information.

[0079] Because the degree of user demand for the master and slave channels is not consistent in different usage scenarios, for example, in application scenarios with fixed usage requirements such as entertainment, office, and emergency communication, the usage priority of the master channel and the usage priority of the slave channel are not in a fixed high-low relationship, that is, the occupancy weight of the master channel and the occupancy weight of the slave channel are not in a fixed large-small relationship, and the determination of the usage priority of the master channel and the usage priority of the slave channel needs to be determined according to the specific usage requirements of the user. Therefore, when determining the confidence corresponding to the online estimated time of each main channel, that is, when determining the desirability corresponding to the online estimated time of each main channel, the specific usage requirements of the user need to be obtained first.

[0080] Among them, the usage demand information carries application scenario information, which can be determined according to the type identifier of the application scenario. The type identifier of the application scenario is used to characterize the uniqueness of the application scenario. For example, the type identifier of the entertainment scenario is "play", and the type identifier of the work scenario is "work". In the entertainment scenario, in order to ensure the user experience, it is necessary to appropriately increase the occupancy weight of the slave channel, and in the work scenario, in order to ensure the basic office needs of the user, it is necessary to appropriately increase the occupancy weight of the main channel. The occupancy weight in this embodiment takes a percentage as an example, and the sum of the main channel occupancy weight and the slave channel occupancy weight is 100%.

[0081] Specifically, after obtaining the user's usage demand information for the target object, the corresponding main channel occupancy weight and the secondary channel occupancy weight are first determined according to the type identifier of the application scenario in the usage demand information. For example, in the working scenario, the corresponding main channel occupancy weight is 80%, and the secondary channel occupancy weight is 20%.

[0082] Step 404: Determine the balance coefficient of the online estimated duration of each main channel according to the fitting relationship.

[0083] According to the fitting relationship between the main channel usage time and the usage frequency obtained in step 304, the estimated usage frequency corresponding to each main channel online estimated time is first determined, and then the balance coefficient is determined according to each main channel online estimated time and the corresponding estimated usage frequency. The balance coefficient is used to characterize the degree to which each online estimated time deviates from the average value of the online estimated time.

[0084] Specifically, the balance coefficient is calculated according to the following calculation formula:

[0085] k=(t0-μ'(t0)) / σ'(t0);

[0086] Where k is the balance coefficient; t0 is the online estimation duration of the main channel; μ' is the average value of the online estimation duration of the main channel; σ' is the variance of the online estimation duration of the main channel.

[0087] For example, taking the estimated online duration of the main channel as 4 minutes, 5 minutes, 6 minutes, 7 minutes and 8 minutes respectively, the corresponding μ'(t0) = 6, σ'(t0)≈1.58 are first calculated, and then the estimated online duration of each main channel is normalized to obtain the balance coefficient corresponding to the estimated online duration of each main channel. For t0=4, k=(4-6) / 1.58=-1.27; k=(5-6) / 1.58=-0.63 when t0=5; k=(6-6) / 1.58=0 when t0=6; k=(7-6) / 1.58=0.63 when t0=7; k=(8-6) / 1.58=1.27 when t0=8.

[0088] Step 406, determining the confidence of the online estimated duration of each main channel according to the balance coefficient, the main channel occupancy weight and the slave channel occupancy weight.

[0089] In order to balance the relationship between the main channel online time and user experience, a balance relationship is set to characterize the balance between the main channel online time and user experience. The expression of the balance relationship is as follows:

[0090] k*α + β;

[0091] Among them, k is the balance coefficient; α is the main channel occupancy weight; β is the slave channel occupancy weight. When the value of k*α + β is the largest, it indicates that the balance between the main channel online duration and user experience has reached the optimal level, indicating that the confidence of the corresponding main channel online estimated duration is the largest at this time, and the main channel online estimated duration with the largest confidence can be determined as the target online estimated duration.

[0092] Exemplarily, taking the above-mentioned main channel online estimated duration as 4min, 5min, 6min, 7min and 8min respectively, the calculated k*α + β values ​​are -0.816, -0.304, 0.2, 0.704 and 1.216 respectively. It can be seen that the maximum value of k*α + β is 1.216, and the corresponding main channel online estimated duration of 8min can be determined as the target online estimated duration.

[0093] In this embodiment, by constructing a balance relationship for characterizing the balance between the main channel online time and the user experience, the balance degrees corresponding to the estimated online time of each main channel are determined, and the maximum balance degree, that is, the estimated online time of the main channel with the best balance effect is determined as the target online estimated time. This helps to ensure the accuracy and reliability of the comparison result when the target online estimated time is subsequently compared with the available power time.

[0094] In one embodiment, as shown in FIG5 , allocating the remaining energy of the power supply according to the comparison result includes:

[0095] Step 502: when the comparison result is that the target online estimated duration is not greater than the power available duration, the remaining energy of the power supply is distributed to the master channel and the slave channel.

[0096] When the target online estimated duration is not greater than the power available duration, it indicates that the remaining power energy is sufficient to support the user's current demand for the main channel. The remaining power energy can be used in the slave channel to facilitate the user to increase the use of additional functions of the target object and improve the user experience. In other words, at this time, the remaining power energy can be allocated to the main channel and the slave channel at the same time, so as to ensure the user's demand for the main channel while improving the user experience.

[0097] Specifically, during allocation, the main channel occupancy weight and the slave channel occupancy weight can be determined respectively according to the type identifier of the application scenario in the usage demand information at this time, and then the main channel occupancy weight is multiplied by the remaining power energy to obtain the power energy that can be allocated to the main channel, and the slave channel occupancy weight is multiplied by the remaining power energy to obtain the power energy that can be allocated to the slave channel, thereby realizing a reasonable allocation of the power energy required for the main channel and the slave channel.

[0098] Step 504: when the comparison result is that the target online estimated duration is greater than the power available duration, the remaining energy of the power supply is allocated to the main channel.

[0099] When the target online estimated duration is greater than the available power duration, it indicates that the remaining power energy is insufficient to support the user's current use needs for the main channel. In this case, the user's use needs for the basic functions of the target object must be met first, and the user experience can be temporarily ignored. That is to say, at this time, all the remaining power energy can be allocated to the main channel to prioritize the user's use needs for the main channel. When the user's use needs change subsequently, consider whether the remaining power energy can improve the user experience.

[0100] In this embodiment, when the target online estimated time is not greater than the power available time, the power energy allocated to the main channel and the power energy of the slave channel are determined respectively according to the main channel occupancy weight and the slave channel occupancy weight corresponding to the application scenario at this time, which helps to meet the user's usage needs while improving the user experience; and when the target online estimated time is greater than the power available time, the remaining power energy is preferentially allocated to the main channel to ensure that the user's usage needs for the basic functions of the target object are met as much as possible. That is to say, this embodiment can achieve a reasonable allocation of the remaining power energy based on the comparison result of the target online estimated time and the power available time, thereby better balancing the use of the main channel and the user experience.

[0101] In one embodiment, determining the available power duration according to the current remaining power energy includes: obtaining the current energy consumption rate of the target object, and determining the available power duration according to the current remaining power energy and the current energy consumption rate.

[0102] When determining the available power time according to the current remaining power and the current energy consumption rate, the result obtained by dividing the remaining power by the current energy consumption rate is mainly determined as the available power time.

[0103] Specifically, the available power supply time can be calculated according to the following formula:

[0104] T0=P0 / P1;

[0105] Where T0 is the available time of the power supply; P0 is the remaining energy of the current power supply; and P1 is the current energy consumption rate.

[0106] Exemplarily, when the current remaining energy P0 of the power supply is 2000 J and the current energy consumption rate P1 is 100 J / min, the available power supply time T0=2000 / 100=20 min.

[0107] In this embodiment, determining the available power supply time based on the current remaining power supply energy and the current energy consumption rate helps to ensure the accuracy of the calculation results of the available power supply time, thereby ensuring the accuracy and reliability of the comparison results obtained when the target online estimated time is subsequently compared with the available power supply time.

[0108] In one embodiment, as shown in FIG6 , the method further includes:

[0109] Step 602: Determine the historical usage duration, historical usage frequency, and historical usage pattern of the main channel within a preset historical period based on the historical usage data.

[0110] By analyzing historical data, we can obtain the actual online distribution of the main channel of users in different time periods and different application scenarios (usage modes). The preset historical period can be the last 12 months, the last month, the last week, etc. In order to ensure the accuracy of the subsequent predicted main channel online estimation time, the preset historical period can be set to a larger time period to ensure sufficient sampling data.

[0111] For example, based on the historical usage data of the target object in the past 7 days, the historical usage duration, historical usage frequency and historical usage pattern are shown in Table 2:

[0112]

[0113] Table 2

[0114] Step 604 , obtaining a duration prediction model for the target object, inputting the historical usage duration, historical usage frequency, and historical usage pattern of the main channel into the time series model, and obtaining the online estimated durations of multiple main channels.

[0115] In order to accurately predict the duration, a duration prediction model can be used for prediction. Specifically, in this embodiment, ARIMA (autoregressive integrated moving average model) is used as an example for time series prediction. The parameters of the ARIMA model are:

[0116] ARIMA (p, d, q);

[0117] Where p is the number of autoregressive terms; d is the difference order; and q is the number of moving average terms.

[0118] For example, assume that through model selection and parameter adjustment, a suitable ARIMA model parameter is determined to be ARIMA (1,1,1), and then the following historical usage data is input into the forecasting model:

[0119] Historical usage duration [60, 50, 70, 45, 80, 55, 75];

[0120] Historical usage frequency [10, 8, 12, 9, 11, 7, 13], which can also be replaced by the percentage of occurrence;

[0121] Historical application scenarios: video conferencing, document editing, data analysis, web browsing, and video playback.

[0122] After the model training is completed, predictions are made based on the current usage demand or the duration of use of the main channel, and the estimated online durations of multiple main channels are obtained, which are 66, 70, and 76 respectively.

[0123] In this embodiment, by collecting historical usage data, determining historical application scenarios, obtaining a duration prediction model for the target object, and inputting historical data into a time series model, a more accurate online estimated duration of the main channel can be obtained. This allows the system to determine the corresponding online estimated duration of the main channel based on the duration of use of the current main channel without obtaining clear usage demand information from the user, thereby achieving a reasonable allocation of the remaining energy of the power supply.

[0124] This embodiment adopts the above method, first determines the available power supply time according to the current remaining power supply energy, then determines the confidence corresponding to each main channel online estimated time according to the fitting relationship, and determines the main channel online estimated time corresponding to the maximum confidence as the final main channel online estimated time, which helps to improve the reliability of subsequent comparison results, thereby improving the rationality and reliability of the allocation of the remaining power supply energy, and further helps to achieve a balance between the main channel online time and user experience.

[0125] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0126] Based on the same inventive concept, the embodiment of the present application also provides an energy allocation device for a dual-channel wireless device for implementing the energy allocation method for the dual-channel wireless device involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the energy allocation device embodiments of one or more dual-channel wireless devices provided below can refer to the limitations of the energy allocation method for the dual-channel wireless device above, and will not be repeated here.

[0127] In one embodiment, as shown in FIG. 7 , an energy distribution device for a dual-channel wireless device is provided, including: a target object data acquisition module 702, an online estimated duration determination module 704, and a power supply residual energy distribution module 706, wherein:

[0128] The target object data acquisition module 702 is used to obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determine the available power time according to the current remaining power;

[0129] The online estimated duration determination module 704 is used to determine the confidence corresponding to the online estimated duration of each main channel according to the fitting relationship, and determine the online estimated duration of the main channel corresponding to the maximum confidence as the target online estimated duration;

[0130] The power supply remaining energy allocation module 706 is used to compare the target online estimated duration with the power supply available duration, obtain a comparison result, and allocate the power supply remaining energy according to the comparison result.

[0131] In one embodiment, the target object data acquisition module 702 is also used to: obtain historical usage data of the target object, the historical usage data including historical usage duration and its corresponding usage frequency; fit the historical usage data according to a preset data fitting strategy to obtain a fitting relationship between the main channel usage duration and usage frequency.

[0132] In one embodiment, the online estimated duration determination module 704 is also used to: obtain the usage demand information of the target object, and determine the main channel occupancy weight and the slave channel occupancy weight according to the usage demand information; determine the balance coefficient of the online estimated duration of each main channel according to the fitting relationship; and determine the confidence of the online estimated duration of each main channel according to the balance coefficient, the main channel occupancy weight and the slave channel occupancy weight.

[0133] In one embodiment, the power supply remaining energy allocation module 706 is also used to: when the comparison result is that the target online estimated time is not greater than the power available time, allocate the remaining power supply energy to the main channel and the slave channel; when the comparison result is that the target online estimated time is greater than the power available time, allocate the remaining power supply energy to the main channel.

[0134] In one embodiment, the target object data acquisition module 702 is further used to: acquire the current energy consumption rate of the target object, and determine the available power supply duration according to the current remaining power of the power supply and the current energy consumption rate.

[0135] In one embodiment, the target object data acquisition module 702 is also used to: determine the historical usage duration, historical usage frequency and historical usage pattern of the main channel within a preset historical period based on historical usage data; obtain the duration prediction model of the target object, input the historical usage duration, historical usage frequency and historical usage pattern of the main channel into the time series model, and obtain the online estimated duration of multiple main channels.

[0136] Each module in the energy distribution device of the dual-channel wireless device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0137] In one embodiment, a computer device is provided, which may be a control device, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store historical usage data of the target object, remaining power of the power supply, and other data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for energy distribution of a dual-channel wireless device is implemented.

[0138] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0139] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0140] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0141] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0142] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0143] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0144] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0145] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for allocating energy for a dual-channel wireless device, characterized in that: The method comprises: Obtain the current remaining power energy of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determine the available power time according to the current remaining power energy; Determine the confidence level corresponding to each of the main channel online estimated durations according to the fitting relationship, and determine the main channel online estimated duration corresponding to the maximum confidence level as the target online estimated duration; The target online estimated duration is compared with the available duration of the power supply to obtain a comparison result, and the remaining energy of the power supply is allocated according to the comparison result.

2. The method according to claim 1, characterized in that The method for determining the fitting relationship between the main channel usage time and the usage frequency includes: Acquire historical usage data of the target object, wherein the historical usage data includes historical usage duration and its corresponding historical usage frequency; According to a preset data fitting strategy, the historical usage data is fitted to obtain a fitting relationship between the usage duration and the usage frequency of the main channel.

3. The method according to claim 1, characterized in that Determining the confidence level corresponding to the online estimated duration of each main channel according to the fitting relationship includes: Acquire usage demand information of the target object, and determine a primary channel occupancy weight and a secondary channel occupancy weight according to the usage demand information; Determining a balance coefficient of the online estimated duration of each main channel according to the fitting relationship; The confidence level of the online estimated duration of each of the main channels is determined according to the balance coefficient, the main channel occupancy weight, and the slave channel occupancy weight.

4. The method according to claim 1, characterized in that The allocating the remaining energy of the power supply according to the comparison result includes: When the comparison result is that the target online estimated duration is not greater than the available duration of the power supply, allocating the remaining energy of the power supply to the master channel and the slave channel; When the comparison result is that the target estimated online duration is greater than the available duration of the power supply, the remaining energy of the power supply is allocated to the main channel.

5. The method according to claim 1, characterized in that The determining, according to the current remaining energy of the power supply, the available power supply duration includes: The current energy consumption rate of the target object is obtained, and the available time of the power supply is determined according to the current remaining energy of the power supply and the current energy consumption rate.

6. The method according to claim 1, characterized in that The method further comprises: Determine, based on the historical usage data, the historical usage duration, historical usage frequency, and historical usage pattern of the main channel within a preset historical period; A duration prediction model of the target object is obtained, and the historical usage duration, the historical usage frequency and the historical usage pattern of the main channel are input into the time series model to obtain multiple main channel online estimated durations.

7. An energy distribution device for a dual-channel wireless device, characterized in that: The device comprises: The target object data acquisition module is used to obtain the current remaining power of the target object, the fitting relationship between the main channel usage time and the usage frequency, and the online estimated time of multiple main channels, and determine the available power time according to the current remaining power; An online estimated duration determination module is used to determine the confidence corresponding to each of the main channel online estimated durations according to the fitting relationship, and determine the main channel online estimated duration corresponding to the maximum confidence as the target online estimated duration; The power supply residual energy allocation module is used to compare the target online estimated duration with the power supply available duration to obtain a comparison result, and allocate the power supply residual energy according to the comparison result.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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