Intelligent terminal management method and system and readable storage medium

Abstract

The invention provides an intelligent terminal management method and system and a readable storage medium. The method comprises the steps of obtaining an application program started by a user in a current intelligent terminal; determining a target application program; obtaining the remaining duration of the task being executed from the target application program; obtaining the current residual electric quantity of the intelligent terminal at the current time; predicting a first endurance duration of the current intelligent terminal in the first operation environment through an electric quantity endurance prediction model; predicting a second endurance duration of the current intelligent terminal in a second operation environment through an electric quantity endurance prediction model; and when the residual duration is greater than the first endurance duration and less than the second endurance duration, determining an application program exit scheme through a preset management algorithm, so that the currently executed task of the target application program can be completed. According to the method, intelligent management is performed on the application program to ensure that the currently executed task of the target application program is smoothly completed, and the experience feeling of a user on the intelligent terminal is improved.

Description

Technical Field

[0001] The present invention relates to the field of electronic information technology, and in particular to an intelligent terminal management method, system and readable storage medium. Background Art

[0002] With the advancement of science and technology, the development and growth of mobile Internet, smart terminals (such as smart phones) are becoming more and more popular, and various application software are also being widely used.

[0003] At present, when users need to open some apps on smart terminals, such as watching a video through a video app, or using a map app for navigation, there is usually a continuous playback time or navigation time, that is, the total time to play the video or the total time to navigate to the destination. Although current smart terminals have a power reminder function, they will only give feedback to users whether to enable power saving mode when the power level is below a certain value (such as 20%). However, for some videos or navigations that last longer, even if the smart terminal enters power saving mode when the power level is below a certain value, it still cannot persist in playing the video or navigating to the destination, which will result in a poor user experience. Summary of the invention

[0004] In order to solve at least one of the above technical problems, the present invention proposes a smart terminal management method, system and readable storage medium, which can make intelligent management of other applications of the smart terminal in combination with the time when the target application is executing tasks, so as to ensure that the tasks being executed by the target application can be completed smoothly, thereby improving the user experience of the smart terminal.

[0005] A first aspect of the present invention provides a smart terminal management method, the method comprising:

[0006] Get the applications that the user has opened in the current smart terminal;

[0007] Determine the target application from the opened applications according to the interface display status of the current smart terminal;

[0008] Obtaining the remaining time of the task being executed from the target application;

[0009] Get the remaining power of the current smart terminal at the current time;

[0010] Based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment through a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps the opened application running;

[0011] Based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running;

[0012] Determine whether the remaining time is greater than the first battery life and less than the second battery life. If so, determine an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

[0013] In this solution, the first battery life of the current smart terminal in the first operating environment is predicted by the battery life prediction model, specifically including:

[0014] Build a battery life prediction model;

[0015] Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters;

[0016] The parameter data and the remaining power are input into a power endurance prediction model, and the power endurance prediction model predicts a first endurance duration.

[0017] In this solution, after the first battery life prediction model predicts the first battery life, the method further includes:

[0018] Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time;

[0019] Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value;

[0020] Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value;

[0021] Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal;

[0022] Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold value to a reference database;

[0023] Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output;

[0024] Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference;

[0025] The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value;

[0026] The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

[0027] In this solution, the battery performance and external environment parameters of the reference smart terminal at historical time are characteristically calculated to obtain a first characteristic value; the battery performance and external environment parameters of the current smart terminal at the current time are obtained, and characteristic calculation is performed to obtain a second characteristic value; the first characteristic value of each reference smart terminal is respectively calculated with the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal, specifically including:

[0028] The optimal temperature and humidity for battery operation are preset to be T0 and R0 respectively;

[0029] The battery performance of the reference smart terminal at a historical time is obtained as health Q1, and the external environmental parameters are temperature T1 and humidity H1. The first eigenvalue K1 is calculated by the calculation formula of the first eigenvalue K1=Q1 / F1, where F1=|T1-T0|*|H1-H0|;

[0030] The battery performance of the current smart terminal at the current time is obtained as health Q2, and the external environmental parameters are temperature T2 and humidity H2. The second eigenvalue K2 is calculated by the calculation formula of the second eigenvalue K2=Q2 / F2, where F2=|T2-T0|*|H2-H0|;

[0031] The difference value R based on each reference smart terminal is calculated through the difference calculation formula R=|K2-K1| / K2.

[0032] In this solution, the application exit plan is determined by a preset management algorithm, including:

[0033] It is assumed that n applications are open in addition to the target application;

[0034] Select each application from the n applications in turn to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-1 applications remain open. If so, mark the selected application as selected, and add the selected application to the candidate database as a candidate solution;

[0035] Eliminate the marked selected applications from the n applications, and select every 2 applications from the remaining applications to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-2 applications remain open. If so, mark the selected application as selected, and associate the selected application as a candidate solution to add to the candidate database;

[0036] According to the above method, the applications marked as selected in the previous i-1 steps are removed, and each i application is selected from the remaining applications in turn to exit, and it is predicted whether the battery life of the current smart device is greater than the remaining time when the remaining ni applications remain turned on. If so, the application selected this time is marked as selected, and the application selected this time is associated as a candidate solution and added to the candidate database until the number of remaining applications is less than i after the applications marked as selected in the previous i-1 steps are removed, where n is a positive integer greater than or equal to 1, and i is a positive integer greater than 1 and less than or equal to n;

[0037] The candidate solutions in the candidate database are screened according to a preset optimization algorithm, and the best candidate solution is selected as the final application exit solution.

[0038] In this solution, the candidate solutions in the candidate database are screened according to the preset optimization algorithm, and the best candidate solution is selected as the final application exit solution, which specifically includes:

[0039] Obtaining respectively the number of applications that need to be exited in each candidate solution state, the difference between the battery life of the smart device and the remaining battery life, and the usage frequency of the applications that need to be exited;

[0040] The number of applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the number of applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the quantity surplus item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0041] The difference between the battery life of the smart device under each candidate solution in the candidate database and the remaining time is compared one by one with the difference between the battery life of the smart device under other candidate solutions and the remaining time. If the former is smaller than the latter, the score of the time saving item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0042] The sum of the usage frequencies of the applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the sum of the usage frequencies of the applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the action stop loss item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0043] Compare the candidate solutions in the candidate database in pairs to determine the number of applications that need to be exited, and cumulatively calculate the total score of the quantity savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the difference between the battery life of the smart device and the remaining time, and cumulatively calculate the total score of the time savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the frequency of use of applications that need to be exited, and cumulatively calculate the total score of the action stop loss item of each candidate solution;

[0044] The weights of the preset quantity saving item, time saving item and action stop loss item on selecting the best candidate plan are different;

[0045] The sum of the scores of the quantity saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the quantity saving items; the sum of the scores of the time saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the time saving items; the sum of the scores of the action stop loss items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the action stop loss items;

[0046] The weighted sum of the number saving items, the time saving items, and the action stop loss items of each candidate solution are added together to obtain the overall score of each candidate solution.

[0047] The candidate with the highest overall score in the candidate database is selected as the final application exit solution.

[0048] The second aspect of the present invention further provides an intelligent terminal management system, comprising a memory and a processor, wherein the memory comprises an intelligent terminal management method program, and when the intelligent terminal management method program is executed by the processor, the following steps are implemented:

[0049] Get the applications that the user has opened in the current smart terminal;

[0050] Determine the target application from the opened applications according to the interface display status of the current smart terminal;

[0051] Obtaining the remaining time of the task being executed from the target application;

[0052] Get the remaining power of the current smart terminal at the current time;

[0053] Based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment through a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps the opened application running;

[0054] Based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running;

[0055] Determine whether the remaining time is greater than the first battery life and less than the second battery life. If so, determine an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

[0056] In this solution, the first battery life of the current smart terminal in the first operating environment is predicted by the battery life prediction model, specifically including:

[0057] Build a battery life prediction model;

[0058] Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters;

[0059] The parameter data and the remaining power are input into a power endurance prediction model, and the power endurance prediction model predicts a first endurance duration.

[0060] In this solution, after the first battery life prediction model predicts the first battery life, the smart terminal management method program further implements the following steps when executed by the processor:

[0061] Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time;

[0062] Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value;

[0063] Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value;

[0064] Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal;

[0065] Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold value to a reference database;

[0066] Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output;

[0067] Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference;

[0068] The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value;

[0069] The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

[0070] The third aspect of the present invention further proposes a computer-readable storage medium, which includes an intelligent terminal management method program. When the intelligent terminal management method program is executed by a processor, the steps of the intelligent terminal management method as described above are implemented.

[0071] The present invention proposes a smart terminal management method, system and readable storage medium, which can combine the remaining time of the target application's ongoing task and determine the exit plan of other applications through a preset management algorithm, so that the target application's ongoing task can be completed smoothly, thereby improving the user's experience of the smart terminal.

[0072] Additional aspects and advantages of the present invention will be given in part in the following description, and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1A flow chart of a smart terminal management method of the present invention is shown;

[0074] Figure 2 A block diagram of an intelligent terminal management system of the present invention is shown. DETAILED DESCRIPTION

[0075] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0076] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0077] Figure 1 A flow chart of an intelligent terminal management method of the present invention is shown.

[0078] like Figure 1 As shown, the first aspect of the present invention provides a smart terminal management method, the method comprising:

[0079] S102, obtaining the applications that the user has opened in the current smart terminal;

[0080] S104, determining a target application from opened applications according to the current interface display state of the smart terminal;

[0081] S106, obtaining the remaining time of the task being executed from the target application;

[0082] S108, obtaining the remaining power of the current smart terminal at the current time;

[0083] S110, based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment using a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps an opened application running;

[0084] S112, based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running;

[0085] S114, determining whether the remaining time is greater than the first endurance time and less than the second endurance time, and if so, determining an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

[0086] The smart terminal management method of the present invention can combine the remaining time of the target application's ongoing task and determine the exit plan of other applications through a preset management algorithm, so that the target application's ongoing task can be completed smoothly, thereby improving the user's experience of the smart terminal.

[0087] Make intelligent management of other applications on smart terminals to ensure that the tasks being executed by the target application can be completed smoothly, thereby improving the user experience of the smart terminal.

[0088] It can be understood that the enabled applications may include applications displayed on the interface, or applications that are not displayed on the interface but are running in the background.

[0089] According to a specific embodiment of the present invention, a target application is determined from opened applications according to the interface display status of the current smart terminal, specifically including: obtaining the application currently displayed on the interface of the current smart terminal, and determining whether the displayed application is executing a time-consuming task (such as navigation); if so, setting the application displayed on the interface as the target application.

[0090] According to a specific embodiment of the present invention, if the remaining time is greater than the second battery life, the user is reminded that the current power cannot complete the task; if the remaining time is less than the first battery life, there is no need to exit other applications.

[0091] According to an embodiment of the present invention, predicting a first battery life of the current smart terminal in a first operating environment by using a battery life prediction model specifically includes:

[0092] Build a battery life prediction model;

[0093] Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters;

[0094] The parameter data and the remaining power are input into a power endurance prediction model, and the power endurance prediction model predicts a first endurance duration.

[0095] It is understood that the external environment parameters may include temperature values, humidity values, etc., but are not limited thereto. The battery performance may be the health of the battery of the smart terminal, for example, the health of the battery is 90%, but is not limited thereto.

[0096] According to an embodiment of the present invention, after the first battery life prediction model predicts the first battery life, the method further includes:

[0097] Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time;

[0098] Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value;

[0099] Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value;

[0100] Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal;

[0101] Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold value to a reference database;

[0102] Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output;

[0103] Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference;

[0104] The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value;

[0105] The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

[0106] It can be understood that the present invention predicts the historical monitoring data of the reference smart terminal by using the same battery life prediction model, and calculates the difference between the predicted battery life and the actual battery life, and further averages the battery life differences of the historical monitoring data of multiple reference smart terminals to obtain a battery life correction value. Finally, the battery life correction value is added to the first battery life predicted by the battery life prediction model to obtain a corrected first battery life. The present invention can effectively improve the accuracy of the first battery life prediction, and further facilitates the subsequent more accurate determination of the application exit plan.

[0107] In addition, the present invention also finds data similar to the characteristic values ​​of the current smart terminal from the historical monitoring data of multiple reference smart terminals through feature calculation and comparison, and then eliminates the interference of the historical monitoring data of other parameter smart terminals on the calculation of the battery life correction value, thereby further improving the accuracy of the battery life correction value.

[0108] It can be understood that after the second battery life duration is predicted, a correction method similar to the correction method based on the first battery life duration can be used to perform correction, thereby obtaining a corrected second battery life duration.

[0109] According to an embodiment of the present invention, the battery performance and external environmental parameters of the reference smart terminal at a historical time are characteristically calculated to obtain a first characteristic value; the battery performance and external environmental parameters of the current smart terminal at a current time are obtained, and characteristic calculation is performed to obtain a second characteristic value; the first characteristic value of each reference smart terminal is respectively calculated with the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal, specifically including:

[0110] The optimal temperature and humidity for battery operation are preset to be T0 and R0 respectively;

[0111] The battery performance of the reference smart terminal at a historical time is obtained as health Q1, and the external environmental parameters are temperature T1 and humidity H1. The first eigenvalue K1 is calculated by the calculation formula of the first eigenvalue K1=Q1 / F1, where F1=|T1-T0|*|H1-H0|;

[0112] The battery performance of the current smart terminal at the current time is obtained as health Q2, and the external environmental parameters are temperature T2 and humidity H2. The second eigenvalue K2 is calculated by the calculation formula of the second eigenvalue K2=Q2 / F2, where F2=|T2-T0|*|H2-H0|;

[0113] The difference value R based on each reference smart terminal is calculated through the difference calculation formula R=|K2-K1| / K2.

[0114] According to an embodiment of the present invention, the application program exit scheme is determined by a preset management algorithm, specifically including:

[0115] It is assumed that n applications are open in addition to the target application;

[0116] Select each application from the n applications in turn to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-1 applications remain open. If so, mark the selected application as selected, and add the selected application to the candidate database as a candidate solution;

[0117] Eliminate the marked selected applications from the n applications, and select every 2 applications from the remaining applications to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-2 applications remain open. If so, mark the selected application as selected, and associate the selected application as a candidate solution to add to the candidate database;

[0118] According to the above method, the applications marked as selected in the previous i-1 steps are removed, and each i application is selected from the remaining applications in turn to exit, and it is predicted whether the battery life of the current smart device is greater than the remaining time when the remaining ni applications remain turned on. If so, the application selected this time is marked as selected, and the application selected this time is associated as a candidate solution and added to the candidate database until the number of remaining applications is less than i after the applications marked as selected in the previous i-1 steps are removed, where n is a positive integer greater than or equal to 1, and i is a positive integer greater than 1 and less than or equal to n;

[0119] The candidate solutions in the candidate database are screened according to a preset optimization algorithm, and the best candidate solution is selected as the final application exit solution.

[0120] In a specific embodiment, when the applications marked as selected in the first i-1 steps are eliminated in the above manner, and each i applications are selected from the remaining applications in turn to exit, n is preset to 10. After the applications marked as selected in the first 4 steps are eliminated, it is assumed that there are only 3 applications remaining. At this time, the 3 remaining applications are not enough to perform the operation in step 5, that is, every 5 applications are selected in turn to exit. Then, the selection of candidate solutions is completed in step 5, and the candidate database is the candidate solutions selected in the first 4 steps.

[0121] In a specific embodiment, when selecting every two applications from the remaining applications to exit, n is preset to 5, and they are application A, application B, application C, application D, and application E respectively; the applications marked in step 1 are preset to be application B and application C, and the remaining applications (i.e., unmarked) in step 2 are 3, namely, application A, application D, and application E; at this time, there are 3 combinations of every two applications, namely, combination 1: application A and application D, combination 2: application A and application E, and combination 3: application D and application E. It is necessary to judge the three combinations separately, that is, first select combination 1, and exit application A and application D at the same time. At this time, the opened applications include application B, application C, and application E. It is predicted whether the battery life of the current smart device is greater than the remaining time when the remaining three applications remain opened. If so, the two applications of combination 1 are associated and marked as selected respectively. Similarly, combination 2 and combination 3 are selected in turn, and it is judged respectively when the application of combination 2 or combination 3 is selected to exit, whether the battery life of the current smart device is greater than the remaining time when the remaining applications remain opened. If so, the two applications of combination 2 or 3 are also associated and marked as selected respectively. If not, no marking is performed. When the third step is performed later, it is necessary to completely eliminate the applications marked as selected in the first two steps, and select every three applications from the remaining applications for combination. It can be seen that the first step of the present invention is to exit one application first, and the second step is to exit two applications, and then gradually increase. It can be understood that when performing the third step, you need to select 3 applications to exit. If an application is marked as selected, it means that the application has achieved a battery life greater than the remaining time by exiting a combination of less than 3 applications in the first two steps. Based on the principle of reducing excessive intervention in smart terminals, there is naturally no need to involve the applications marked as selected in the first two steps in the selection of the application exit plan in the third step.

[0122] According to an embodiment of the present invention, the candidate solutions in the candidate database are screened according to a preset optimization algorithm, and the best candidate solution is selected as the final application exit solution, which specifically includes:

[0123] Obtaining respectively the number of applications that need to be exited in each candidate solution state, the difference between the battery life of the smart device and the remaining battery life, and the usage frequency of the applications that need to be exited;

[0124] The number of applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the number of applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the quantity surplus item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0125] The difference between the battery life of the smart device under each candidate solution in the candidate database and the remaining time is compared one by one with the difference between the battery life of the smart device under other candidate solutions and the remaining time. If the former is smaller than the latter, the score of the time saving item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0126] The sum of the usage frequencies of the applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the sum of the usage frequencies of the applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the action stop loss item of the former candidate solution is increased by 1, otherwise, it remains unchanged;

[0127] Compare the candidate solutions in the candidate database in pairs to determine the number of applications that need to be exited, and cumulatively calculate the total score of the quantity savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the difference between the battery life of the smart device and the remaining time, and cumulatively calculate the total score of the time savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the frequency of use of applications that need to be exited, and cumulatively calculate the total score of the action stop loss item of each candidate solution;

[0128] The weights of the preset quantity saving item, time saving item and action stop loss item on selecting the best candidate plan are different;

[0129] The sum of the scores of the quantity saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the quantity saving items; the sum of the scores of the time saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the time saving items; the sum of the scores of the action stop loss items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the action stop loss items;

[0130] The weighted sum of the number saving items, the time saving items, and the action stop loss items of each candidate solution are added together to obtain the overall score of each candidate solution.

[0131] The candidate with the highest overall score in the candidate database is selected as the final application exit solution.

[0132] It can be understood that when it is necessary to exit other applications to ensure that the task of the target application can be successfully completed, it is necessary to exit as few other applications as possible. On the one hand, the evaluation is performed by comparing the number of applications that need to be exited under the candidate solutions, and on the other hand, the evaluation is performed by comparing the difference between the battery life of the smart device and the remaining time under each candidate solution. That is, if exiting two applications has satisfied the battery life of the smart device being greater than the remaining time, if more applications are exited, although the battery life of the smart device can be extended, based on the successful completion of the task of the target application, the transition intervention in the status of the currently enabled applications of the smart device is minimized as much as possible.

[0133] It is understandable that when exiting an application, the frequency of use of each application by the user should also be considered, and the exit of applications with high user frequency should be minimized as much as possible. Therefore, the present invention selects the candidate with the highest overall score as the final application exit solution based on a preset optimization algorithm, combining multiple factors and the influence weight of each factor on the selection.

[0134] Figure 2 A block diagram of an intelligent terminal management system of the present invention is shown.

[0135] like Figure 2 As shown, the second aspect of the present invention further proposes an intelligent terminal management system 2, comprising a memory 21 and a processor 22, wherein the memory comprises an intelligent terminal management method program, and when the intelligent terminal management method program is executed by the processor, the following steps are implemented:

[0136] Get the applications that the user has opened in the current smart terminal;

[0137] Determine the target application from the opened applications according to the interface display status of the current smart terminal;

[0138] Obtaining the remaining time of the task being executed from the target application;

[0139] Get the remaining power of the current smart terminal at the current time;

[0140] Based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment through a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps the opened application running;

[0141] Based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running;

[0142] Determine whether the remaining time is greater than the first battery life and less than the second battery life. If so, determine an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

[0143] According to an embodiment of the present invention, predicting a first battery life of the current smart terminal in a first operating environment by using a battery life prediction model specifically includes:

[0144] Build a battery life prediction model;

[0145] Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters;

[0146] The parameter data and the remaining power are input into a power endurance prediction model, and the power endurance prediction model predicts a first endurance duration.

[0147] According to an embodiment of the present invention, after the first battery life duration is predicted by the battery life prediction model, the smart terminal management method program further implements the following steps when executed by the processor:

[0148] Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time;

[0149] Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value;

[0150] Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value;

[0151] Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal;

[0152] Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold value to a reference database;

[0153] Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output;

[0154] Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference;

[0155] The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value;

[0156] The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

[0157] The third aspect of the present invention further proposes a computer-readable storage medium, which includes an intelligent terminal management method program. When the intelligent terminal management method program is executed by a processor, the steps of the intelligent terminal management method as described above are implemented.

[0158] The smart terminal management method, system and readable storage medium proposed in the present invention can combine the remaining time of the target application's ongoing task and determine the exit plan of other applications through a preset management algorithm, so that the target application's ongoing task can be completed smoothly, thereby improving the user's experience of the smart terminal.

[0159] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0160] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0161] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0162] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0163] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0164] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A smart terminal management method, characterized in that: The method comprises: Get the applications that the user has opened in the current smart terminal; Determine the target application from the opened applications according to the interface display status of the current smart terminal; Obtaining the remaining time of the task being executed from the target application; Get the remaining power of the current smart terminal at the current time; Based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment through a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps the opened application running; Based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running; Determine whether the remaining time is greater than the first battery life and less than the second battery life. If so, determine an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

2. The intelligent terminal management method according to claim 1, characterized in that: The battery life prediction model is used to predict the first battery life of the current smart terminal in the first operating environment, specifically including: Build a battery life prediction model; Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters; The parameter data and the remaining power are input into a battery life prediction model, and the battery life prediction model predicts a first battery life duration.

3. A smart terminal management method according to claim 2, characterized in that: After the battery life prediction model predicts the first battery life, the method further includes: Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time; Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value; Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value; Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal; Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold into a reference database; Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output; Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference; The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value; The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

4. The intelligent terminal management method according to claim 3, characterized in that: Performing characteristic calculation on the battery performance and external environment parameters of the reference smart terminal at a historical time to obtain a first characteristic value; Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value; The difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal is calculated to obtain a difference value based on each reference smart terminal, specifically including: The optimal temperature and humidity for battery operation are preset to be T0 and R0 respectively; The battery performance of the reference smart terminal at a historical time is obtained as health Q1, and the external environmental parameters are temperature T1 and humidity H1. The first eigenvalue K1 is calculated by the calculation formula of the first eigenvalue K1=Q1 / F1, where F1=|T1-T0|*|H1-H0|; The battery performance of the current smart terminal at the current time is obtained as health Q2, and the external environmental parameters are temperature T2 and humidity H2. The second eigenvalue K2 is calculated by the calculation formula of the second eigenvalue K2=Q2 / F2, where F2=|T2-T0|*|H2-H0|; The difference value R based on each reference smart terminal is calculated through the difference calculation formula R=|K2-K1| / K2.

5. The intelligent terminal management method according to claim 1, characterized in that: The application exit plan is determined through a preset management algorithm, including: It is assumed that n applications are open in addition to the target application; Select each application from the n applications in turn to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-1 applications remain open. If so, mark the selected application as selected, and add the selected application to the candidate database as a candidate solution; Eliminate the marked selected applications from the n applications, and select every 2 applications from the remaining applications to exit, and predict whether the battery life of the current smart device is greater than the remaining time when the remaining n-2 applications remain open. If so, mark the selected application as selected, and associate the selected application as a candidate solution to add to the candidate database; According to the above method, the applications marked as selected in the previous i-1 steps are removed, and each i application is selected from the remaining applications in turn to exit, and it is predicted whether the battery life of the current smart device is greater than the remaining time when the remaining ni applications remain turned on. If so, the application selected this time is marked as selected, and the application selected this time is associated as a candidate solution and added to the candidate database until the number of remaining applications is less than i after the applications marked as selected in the previous i-1 steps are removed, where n is a positive integer greater than or equal to 1, and i is a positive integer greater than 1 and less than or equal to n; The candidate solutions in the candidate database are screened according to a preset optimization algorithm, and the best candidate solution is selected as the final application exit solution.

6. A smart terminal management method according to claim 5, characterized in that: The candidate solutions in the candidate database are screened according to the preset optimization algorithm, and the best candidate solution is selected as the final application exit solution, including: Obtaining respectively the number of applications that need to be exited in each candidate solution state, the difference between the battery life of the smart device and the remaining battery life, and the usage frequency of the applications that need to be exited; The number of applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the number of applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the quantity surplus item of the former candidate solution is increased by 1, otherwise, it remains unchanged; The difference between the battery life of the smart device under each candidate solution in the candidate database and the remaining time is compared one by one with the difference between the battery life of the smart device under other candidate solutions and the remaining time. If the former is smaller than the latter, the score of the time saving item of the former candidate solution is increased by 1, otherwise, it remains unchanged; The sum of the usage frequencies of the applications that need to be withdrawn under each candidate solution in the candidate database is compared one by one with the sum of the usage frequencies of the applications that need to be withdrawn under the remaining candidate solutions. If the former is less than the latter, the score of the action stop loss item of the former candidate solution is increased by 1, otherwise, it remains unchanged; Compare the candidate solutions in the candidate database in pairs to determine the number of applications that need to be exited, and cumulatively calculate the total score of the quantity savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the difference between the battery life of the smart device and the remaining time, and cumulatively calculate the total score of the time savings item of each candidate solution; compare the candidate solutions in the candidate database in pairs to determine the frequency of use of applications that need to be exited, and cumulatively calculate the total score of the action stop loss item of each candidate solution; The influence weights of the preset quantity saving item, time saving item and action stop loss item on the selection of the best candidate plan are different; The sum of the scores of the quantity saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the quantity saving items; the sum of the scores of the time saving items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the time saving items; the sum of the scores of the action stop loss items of each candidate solution is multiplied by the corresponding influence weight to obtain the sum of the score weights of the action stop loss items; The weighted sum of the number saving items, the time saving items, and the action stop loss items of each candidate solution are added together to obtain the overall score of each candidate solution. The candidate with the highest overall score in the candidate database is selected as the final application exit solution.

7. An intelligent terminal management system, characterized in that: The invention comprises a memory and a processor, wherein the memory comprises a smart terminal management method program, and when the smart terminal management method program is executed by the processor, the following steps are implemented: Get the applications that the user has opened in the current smart terminal; Determine the target application from the opened applications according to the interface display status of the current smart terminal; Obtaining the remaining time of the task being executed from the target application; Get the remaining power of the current smart terminal at the current time; Based on the remaining power, predicting a first battery life of the current smart terminal in a first operating environment through a power life prediction model, wherein the first operating environment refers to an environment in which the current smart terminal keeps the opened application running; Based on the remaining power, predicting a second battery life of the current smart terminal in a second operating environment through a power life prediction model, wherein the second operating environment refers to an environment in which the current smart terminal keeps only the target application running; Determine whether the remaining time is greater than the first battery life and less than the second battery life. If so, determine an application exit plan for the opened application through a preset management algorithm so that the executing task of the target application can be completed.

8. The intelligent terminal management system according to claim 7, characterized in that: The battery life prediction model is used to predict the first battery life of the current smart terminal in the first operating environment, specifically including: Build a battery life prediction model; Acquire parameter data that affects the battery life of the current smart terminal, the parameter data at least including the battery performance of the current smart terminal at the current time, the power consumption properties of each application in the first operating environment, and external environment parameters; The parameter data and the remaining power are input into a battery life prediction model, and the battery life prediction model predicts a first battery life duration.

9. The intelligent terminal management system according to claim 8, characterized in that: After the first battery life duration is predicted by the battery life prediction model, the smart terminal management method program further implements the following steps when executed by the processor: Obtain historical monitoring data of multiple reference smart terminals, each historical monitoring data at least including battery performance, remaining power, external environmental parameters, power consumption properties of opening applications, and actual battery life of the reference smart terminal at a historical time; Based on the historical monitoring data of each reference smart terminal, characteristic calculation is performed on the battery performance and external environmental parameters of the reference smart terminal at a historical time to obtain a first characteristic value; Obtaining the battery performance and external environment parameters of the current smart terminal at the current time, and performing feature calculation to obtain a second feature value; Calculate the difference between the first characteristic value of each reference smart terminal and the second characteristic value of the current smart terminal to obtain a difference value based on each reference smart terminal; Adding historical monitoring data of reference smart terminals whose difference values ​​are less than a second threshold into a reference database; Based on the historical monitoring data of each reference smart terminal in the reference database, the battery performance, remaining power, external environmental parameters, and power consumption attributes of the reference smart terminal at historical times are input into the power endurance prediction model, and the predicted endurance is output; Based on the historical monitoring data of each reference smart terminal in the reference database, the actual battery life is subtracted from the predicted battery life to obtain the battery life difference; The battery life differences of the historical monitoring data of all reference smart terminals in the reference database are added to obtain the total battery life differences, and the total battery life differences are divided by the total amount of historical monitoring data of the reference smart terminals in the reference database to obtain the average battery life difference as the battery life correction value; The battery life prediction model predicts the first battery life, and then adds the battery life correction value to obtain the corrected first battery life.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a smart terminal management method program. When the smart terminal management method program is executed by a processor, the steps of the smart terminal management method according to any one of claims 1 to 6 are implemented.

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