Tablet screen power saving control method and system based on user behavior analysis

Abstract

The application relates to a tablet screen power saving control method and system based on user behavior analysis. The method comprises the following steps: reading sleep data of a user, obtaining a sleep starting time range of the user habit, and defining the sleep starting time range as a sleep prediction window; when the system time enters the sleep prediction window and the tablet computer is detected to be in a user use state, a preset screen downgrade test operation is actively performed, and the operation at least comprises reducing screen brightness and / or reducing screen refresh rate; in a preset monitoring period, whether there is active correction behavior of the user to the screen downgrade test operation is monitored in real time; if not, the tablet computer state is marked as a pre-sleep state; in the pre-sleep state, gyroscope data is continuously read, and whether motion data mutation representing device hand-off occurs is identified; when the motion data mutation is identified, it is determined that the user has entered a sleep state; after it is determined that the user has entered the sleep state, the current time is recorded to update the sleep data.

Description

Technical Field

[0001] This application relates to the field of tablet computer technology, and in particular to a method, system, computer device, storage medium, and computer program product for controlling screen power saving of a tablet computer based on user behavior analysis. Background Technology

[0002] As a portable multimedia terminal, the screen is the most power-consuming component of a tablet computer. Existing screen power-saving technologies can be mainly categorized as follows: One approach is a screen-off strategy based on a fixed timeout. The system automatically reduces brightness or turns off the screen after a fixed period of inactivity. This method is simple, but prone to misjudgment: in scenarios where users are reading long articles or watching videos for extended periods without touch input, the screen may dim or turn off inappropriately, severely impacting the user experience.

[0003] The second approach is a gaze-based detection scheme. This scheme uses the front-facing camera to capture the user's face or eye direction, and performs power-saving actions when the user's gaze leaves the screen. However, this scheme performs poorly in low-light environments, and keeping the camera constantly on raises privacy concerns and generates additional power consumption.

[0004] Thirdly, there is a dynamic timeout scheme based on predictive operation behavior. This scheme learns users' operation interval habits and adaptively adjusts the screen timeout. However, this method still belongs to the "passive waiting" mode, meaning it only intervenes after the user has been inactive for a period of time, and cannot proactively or in advance determine changes in user intent.

[0005] Fourthly, there is a scene recognition solution based on sensor fusion. This solution uses accelerometers, gyroscopes, and other sensors to determine whether the user is stationary, walking, or riding in a vehicle, and then matches the corresponding power strategy. However, existing solutions cannot precisely distinguish between two seemingly similar but drastically different states: "the user is using the device but is stationary" and "the user is asleep and the device has naturally been released from their hand."

[0006] In summary, existing technologies lack a method that can proactively, accurately, and non-intrusively determine whether a user is ready to fall asleep or has already fallen asleep, and execute deep power-saving controls accordingly. Summary of the Invention

[0007] The purpose of this invention is to provide a tablet computer screen power-saving control method and system based on user behavior analysis, so as to solve the problem that the existing technology is difficult to accurately and non-disturbingly identify the user's intention to fall asleep and execute deep power saving in a timely manner.

[0008] In a first aspect, this application provides a method for controlling power saving on a tablet computer screen based on user behavior analysis, the method comprising: Sleep window acquisition steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; Trial execution steps: When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. User feedback monitoring steps: During the preset monitoring period, monitor in real time whether there is any active corrective behavior from the user in probing the screen downgrade; if the active corrective behavior is detected, terminate the current power saving control process and restore the screen to the state before downgrade; if not detected, mark the tablet computer state as a pre-sleep state. Physical state confirmation steps: In the pre-sleep state, continuously read gyroscope data and identify whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state; Deep power saving execution steps: After determining that the user has entered a sleep state, record the current time to update the sleep data, and start a confirmation timer. If the gyroscope data does not change within the duration set by the confirmation timer, then perform deep power saving operation, which includes at least terminating currently running unnecessary programs and turning off the screen.

[0009] In one embodiment, "reading the user's sleep data" specifically includes: reading the user's set bedtime from a local health data interface; or, obtaining the user's sleep history through a wearable device bound to the tablet; or, reading from a user behavior prediction model trained locally on the tablet, which is generated by learning the user's long-term multi-dimensional usage habit data, the multi-dimensional usage habit data including at least the timestamp of the last time the screen was turned off each day and the operation frequency in the last hour before the screen was turned off. In one embodiment, "active correction behavior" includes at least one or a combination of the following: within a preset time period, detecting a user's operation to increase brightness via a brightness adjustment control on a touchscreen; detecting that after the user's screen degradation trial operation, continuous touch swiping or clicking behavior exceeding a preset frequency threshold is triggered; and detecting the user's return of gaze to the screen via a front-facing camera.

[0010] In one embodiment, "identifying whether a motion data mutation representing the device being released from the hand" specifically involves: calculating the mean square error of the gyroscope's three-axis angular velocity data within a sliding time window; if the mean square error exceeds a preset mutation threshold, then determining that the motion data mutation has occurred; or, inputting the real-time gyroscope data stream into a trained lightweight neural network model; when the confidence level of the "release / fall" event classification output by the model exceeds a preset threshold, determining that the motion data mutation has occurred.

[0011] In one embodiment, “performing a deep power-saving operation” is performed as follows: first, a lock screen key command is simulated to put the currently running program into a background suspension state; after the confirmation timer expires, the background suspension non-critical programs are cleared one by one, and finally the screen is turned off.

[0012] In one embodiment, "detecting that the tablet computer is in user use" specifically includes: the screen being on and meeting at least one of the following conditions: an application supporting user interaction is running in the foreground; a touch input event is detected within a recent preset time period; or audio or video content is being played through the system audio interface.

[0013] In one embodiment, during the screen degradation trial operation, the reduction in screen brightness and / or screen refresh rate is gradual; after the trial execution step is initiated, the system gradually adjusts the screen brightness and / or refresh rate to the target value within a preset time period in a step-by-step or continuous slow-down manner.

[0014] In one embodiment, before the sleep window acquisition step, there is also an enable condition judgment step: detecting the current power supply mode and battery level of the tablet computer. If the tablet computer is in an external power supply state, or the battery level is higher than a preset safety threshold, then the subsequent steps of the method are not started.

[0015] Secondly, this application also provides a tablet computer screen power-saving control system based on user behavior analysis, the system comprising: Sleep data reading module: Used to obtain the user's habitual sleep start time range and define it as a sleep prediction window; Trial control module: When the system time enters the sleep prediction window and the tablet is detected to be in user mode, actively reduce the screen brightness and / or screen refresh rate; Feedback monitoring module: Used to monitor the user's proactive corrective behavior in real time after the screen is downgraded. If no corrective behavior is detected, a pre-sleep state signal is triggered. Physical state confirmation module: Connected to a gyroscope, used to analyze gyroscope data to identify sudden release after receiving the pre-sleep state signal, and generate a sleep confirmation signal when it is detected; Energy-saving execution and learning module: Used to receive the sleep confirmation signal, record the time to update the user's sleep habits in the sleep data reading module, and perform deep power-saving operations such as turning off the screen and clearing background programs after a delay to confirm that there are no subsequent actions.

[0016] Thirdly, this application also provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. During the preset monitoring period, the system monitors in real time whether there is any active corrective behavior from the user in probing the screen downgrade. If such active corrective behavior is detected, the current power-saving control process is terminated and the screen is restored to its state before downgrade. If no such behavior is detected, the tablet computer is marked as being in a pre-sleep state. In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. After determining that the user has entered a sleep state, the current time is recorded to update the sleep data, and a confirmation timer is started. If the gyroscope data does not change within the time set by the confirmation timer, a deep power-saving operation is performed, which includes at least terminating currently running non-essential programs and turning off the screen.

[0017] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. During the preset monitoring period, the system monitors in real time whether there is any active corrective behavior from the user in probing the screen downgrade. If such active corrective behavior is detected, the current power-saving control process is terminated and the screen is restored to its state before downgrade. If no such behavior is detected, the tablet computer is marked as being in a pre-sleep state. In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. After determining that the user has entered a sleep state, the current time is recorded to update the sleep data, and a confirmation timer is started. If the gyroscope data does not change within the time set by the confirmation timer, a deep power-saving operation is performed, which includes at least terminating currently running non-essential programs and turning off the screen.

[0018] Fifthly, this application also provides a computer program product comprising a computer program that, when executed by a processor, performs the following steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. During the preset monitoring period, the system monitors in real time whether there is any active corrective behavior from the user in probing the screen downgrade. If such active corrective behavior is detected, the current power-saving control process is terminated and the screen is restored to its state before downgrade. If no such behavior is detected, the tablet computer is marked as being in a pre-sleep state. In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. After determining that the user has entered a sleep state, the current time is recorded to update the sleep data, and a confirmation timer is started. If the gyroscope data does not change within the time set by the confirmation timer, a deep power-saving operation is performed, which includes at least terminating currently running non-essential programs and turning off the screen.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Accurate Judgment, Seamless Experience: A "gentle probing" approach is used instead of direct interruption. By slightly reducing brightness / refresh rate and observing user feedback, the system can accurately distinguish between users who are "awake" and those who are "preparing to sleep," avoiding experience interruptions caused by misjudgment. 2. Physical confirmation, fast and reliable: Utilizing the physical action of "removing the device from the hand," which is highly correlated with falling asleep, as the core judgment criterion, it is faster and more accurate than the traditional "long period of stillness" detection, and significantly reduces the probability of false judgment; 3. Closed-loop learning, becoming smarter with use: Each time a sleep condition is successfully determined, the actual sleep time is fed back to the sleep data model to complete self-learning and optimization, so that the sleep window prediction becomes more in line with the user's real schedule over time. 4. Deep energy saving and security protection: After confirming sleep, it not only turns off the screen, but also actively cleans up unnecessary programs running in the background, avoiding unnecessary power consumption and data and privacy risks caused by background application activities. Attached Figure Description

[0020] Figure 1 This is a flowchart of the main steps of the method of the present invention.

[0021] Figure 2 This is a schematic diagram illustrating sleep window prediction and dynamic learning update in one embodiment of the present invention.

[0022] Figure 3 This is a modular structure block diagram of the system of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] A method for power saving control of tablet computer screens based on user behavior analysis, the method comprising: Sleep window acquisition steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; Trial execution steps: When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. User feedback monitoring steps: During the preset monitoring period, monitor in real time whether there is any active corrective behavior from the user in probing the screen downgrade; if the active corrective behavior is detected, terminate the current power saving control process and restore the screen to the state before downgrade; if not detected, mark the tablet computer state as a pre-sleep state. Physical state confirmation steps: In the pre-sleep state, continuously read gyroscope data and identify whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state; Deep power saving execution steps: After determining that the user has entered a sleep state, record the current time to update the sleep data, and start a confirmation timer. If the gyroscope data does not change within the duration set by the confirmation timer, then perform deep power saving operation, which includes at least terminating currently running unnecessary programs and turning off the screen.

[0025] Specifically, "reading the user's sleep data" includes: reading the user's set bedtime from a local health data interface; or obtaining the user's sleep history through a wearable device bound to the tablet; or reading from a user behavior prediction model trained locally on the tablet, which is generated by learning from the user's long-term multi-dimensional usage habit data, including at least the timestamp of the last time the screen was turned off each day and the frequency of operation in the last hour before the screen was turned off. Specifically, "proactive corrective behavior" includes at least one or a combination of the following: Within a preset time period, the system detects that the user has increased the brightness by adjusting the brightness control via the touchscreen. After the user's screen degradation attempt was detected, continuous touch swipes or clicks exceeding a preset frequency threshold were triggered. The system detects the user's gaze returning to the screen using the front-facing camera.

[0026] Specifically, "identifying whether abrupt changes occur in motion data characterizing device release" includes: Calculate the mean square error of the gyroscope's three-axis angular velocity data within the sliding time window. If the mean square error exceeds a preset mutation threshold, it is determined that a mutation has occurred in the motion data. Alternatively, the real-time gyroscope data stream can be input into a trained lightweight neural network model. When the confidence level of the "drop / fall" event classification output by the model exceeds a preset threshold, the motion data mutation is determined to have occurred.

[0027] Specifically, “performing deep power-saving operations” includes: first, simulating the lock screen key command to put the currently running program into a background suspension state; after the confirmation timer expires, clearing the background suspension non-critical programs one by one, and finally turning off the screen.

[0028] Specifically, "detecting that the tablet is in user use" includes: the screen is on, and at least one of the following conditions is met: The foreground runs an application that supports user interaction; Touch input events were detected within the most recent preset time period; Audio or video content is being played through the system audio interface.

[0029] Specifically, during the screen downgrade trial operation, the reduction in screen brightness and / or screen refresh rate is gradual. After the trial execution step is initiated, the system gradually adjusts the screen brightness and / or refresh rate to the target value within a preset time period in a step-by-step or continuous slow-down manner.

[0030] Specifically, before the sleep window acquisition step, there is also an enable condition judgment step: detecting the tablet's current power supply mode and battery level. If the tablet is powered by an external power source, or the battery level is higher than a preset safety threshold, then the subsequent steps of the method will not be initiated. Example 1

[0031] Figure 1 The overall flow of the method in this embodiment is illustrated. In a typical "using a tablet before bed" scenario, the flow is executed according to the following steps: Step S1: Obtain and enable sleep window.

[0032] The system first checks the tablet's power supply status and battery level. If it is currently powered by battery and the battery level is below 80%, the subsequent processes will begin.

[0033] Subsequently, the sleep data reading module retrieves data from the local user behavior prediction model. This model analyzes the timestamp of the last manual screen lock each day over the past 30 days and the frequency of screen operations in the preceding hour, clustering to determine that the user's habitual sleep start time range is "23:30 to 00:00", and uses this as the sleep prediction window for the day.

[0034] Step S2, tentative execution.

[0035] The current system time is 23:45, falling within the sleep prediction window. The system detected that the user is using a reading application, with the screen lit and exhibiting regular page-turning touch events, which is determined to be the "user usage state".

[0036] The testing control module then initiated a screen degradation test: within 30 seconds, the screen brightness was gradually reduced from the current 60% to 40% in steps, while the screen refresh rate was reduced from 120Hz to 60Hz. This change was subtle and gradual, designed to avoid causing strong aversion to alert users.

[0037] Step S3: User feedback monitoring.

[0038] During the two-minute monitoring period following the downgrade completion, the feedback monitoring module continuously listens for user-initiated corrective actions. At this time, the user may react in two ways: When the user is awake: The user notices the screen dimming and increases the brightness to 70% via the pull-down control center. The system immediately recognizes this brightness increase, deems it an "active correction behavior," terminates the power-saving process, and restores the brightness and refresh rate to 60% and 120Hz respectively, the pre-downgrade levels, within 1 second. This process ends.

[0039] When the user is in a sleep-like state: The user is already drowsy and is still mechanically swiping the screen, but is not making any adjustments to the reduced brightness or refresh rate. No proactive corrective actions are detected during the monitoring period, and the system marks the tablet's state as "pre-sleep state".

[0040] Step S4, physical status confirmation.

[0041] In the "pre-sleep state," the physical state confirmation module continuously analyzes the gyroscope's real-time data stream. Specifically, it calculates the mean square error of the three-axis angular velocities within a 500-millisecond sliding window. Afterward, the user's arm muscles completely relax, and the tablet slides from their hand onto the bed sheet. This action causes a dramatic fluctuation in the gyroscope data within a very short time, and the calculated mean square error of the angular velocity instantly exceeds a preset abrupt change threshold.

[0042] The system recognizes this "mutation in motion data," determines that the user has entered a sleep state, and records the current timestamp.

[0043] Step S5: Deep power saving execution and learning.

[0044] The system generates a sleep confirmation signal. The energy-saving execution module first records the current time "00:05" and feeds it back to the user behavior prediction model in step S1 as the "actual sleep time" to update its parameters and make the sleep prediction window for the next day more accurate.

[0045] Simultaneously, the module started a one-minute confirmation timer. Since the tablet was laid flat on the sheet, the gyroscope data remained stable during the timer's duration, without any further abrupt changes.

[0046] After the timer expires, the module performs deep power saving: first, it simulates pressing the lock screen button once to put the reading application into a background suspension state (to ensure data security); then, it terminates non-critical system processes such as background audio and video playback services and social application synchronization in turn; finally, it turns off the screen backlight to put the tablet into deep sleep mode.

[0047] Example 2

[0048] In this embodiment, the source of sleep data is different. The user wears a smartwatch paired with a tablet, and its sleep history shows that the user's average bedtime is 1:00 AM. In step S1, the system reads this data through the API interface and sets the sleep prediction window to "00:45 to 01:15". The remaining steps are similar to those in embodiment 1.

[0049] Example 3

[0050] This embodiment uses a different method to identify "dropping hands". In step S4, the physical state confirmation module incorporates a pre-trained lightweight recurrent neural network model. This model directly takes the real-time six-axis data stream (three-axis angular velocity + three-axis acceleration) from the gyroscope as input and outputs an event classification in real time. When the model outputs the "dropping hands" category with a confidence level exceeding 0.9, the system triggers a sleep determination. This method is more robust to identifying the complex physical process of "dropping hands".

[0051] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0052] Based on the same inventive concept, this application also provides a tablet computer screen power-saving control system based on user behavior analysis for implementing the aforementioned tablet computer screen power-saving control method based on user behavior analysis. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more embodiments of the tablet computer screen power-saving control system based on user behavior analysis provided below can be found in the limitations of the tablet computer screen power-saving control method based on user behavior analysis described above, and will not be repeated here.

[0053] In one embodiment, such as Figure 2 As shown, a tablet computer screen power-saving control system based on user behavior analysis is provided, including: a sleep data reading module, a trial control module, a feedback monitoring module, a physical state confirmation module, and an energy-saving execution and learning module, wherein: The sleep data reading module is used to obtain the user's habitual sleep start time range and define it as the sleep prediction window; The probe control module is used to actively reduce the screen brightness and / or screen refresh rate when the system time enters the sleep prediction window and the tablet computer is detected to be in user use mode. The feedback monitoring module is used to monitor the user's proactive corrective behavior in real time after the screen is downgraded. If no corrective behavior is detected, a pre-sleep state signal is triggered. The physical state confirmation module, connected to the gyroscope, is used to analyze the gyroscope data to identify sudden changes in hand release after receiving the pre-sleep state signal, and generate a sleep confirmation signal when such changes are detected. The energy-saving execution and learning module is used to receive the sleep confirmation signal, record the time to update the user's sleep habits in the sleep data reading module, and perform a deep power-saving operation of turning off the screen and clearing background programs after a delay to confirm that there are no subsequent actions.

[0054] The various modules in the aforementioned user behavior analysis-based tablet computer screen power-saving control system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0055] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps: Sleep window acquisition steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; Trial execution steps: When the system time enters the sleep prediction window and the tablet computer is detected to be in user use state, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. User feedback monitoring steps: During the preset monitoring period, monitor in real time whether there is any active corrective behavior from the user in probing the screen downgrade; if the active corrective behavior is detected, terminate the current power saving control process and restore the screen to the state before downgrade; if not detected, mark the tablet computer state as a pre-sleep state. Physical state confirmation steps: In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. Deep power saving execution steps: After determining that the user has entered a sleep state, record the current time to update the sleep data, and start a confirmation timer. If the gyroscope data does not change within the time set by the confirmation timer, then perform deep power saving operation, which includes at least terminating currently running unnecessary programs and turning off the screen.

[0056] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor: Sleep window acquisition steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; Trial execution steps: When the system time enters the sleep prediction window and the tablet computer is detected to be in user use state, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. User feedback monitoring steps: During the preset monitoring period, monitor in real time whether there is any active corrective behavior from the user in probing the screen downgrade; if the active corrective behavior is detected, terminate the current power saving control process and restore the screen to the state before downgrade; if not detected, mark the tablet computer state as a pre-sleep state. Physical state confirmation steps: In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. Deep power saving execution steps: After determining that the user has entered a sleep state, record the current time to update the sleep data, and start a confirmation timer. If the gyroscope data does not change within the time set by the confirmation timer, then perform deep power saving operation, which includes at least terminating currently running unnecessary programs and turning off the screen.

[0057] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: Sleep window acquisition steps: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; Trial execution steps: When the system time enters the sleep prediction window and the tablet computer is detected to be in user use state, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. User feedback monitoring steps: During the preset monitoring period, monitor in real time whether there is any active corrective behavior from the user in probing the screen downgrade; if the active corrective behavior is detected, terminate the current power saving control process and restore the screen to the state before downgrade; if not detected, mark the tablet computer state as a pre-sleep state. Physical state confirmation steps: In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. Deep power saving execution steps: After determining that the user has entered a sleep state, record the current time to update the sleep data, and start a confirmation timer. If the gyroscope data does not change within the time set by the confirmation timer, then perform deep power saving operation, which includes at least terminating currently running unnecessary programs and turning off the screen.

[0058] 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, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0059] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media 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), magnetic 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. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0060] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0061] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A power-saving control method for tablet computer screens based on user behavior analysis, characterized in that, The method includes: Read the user's sleep data, obtain the user's habitual sleep start time range, and define it as the sleep prediction window; When the system time enters the sleep prediction window and the tablet is detected to be in user use mode, a preset screen degradation trial operation is actively executed. The operation includes at least reducing screen brightness and / or reducing screen refresh rate. During the preset monitoring period, the system monitors in real time whether there is any active corrective behavior from the user in probing the screen downgrade. If such active corrective behavior is detected, the current power-saving control process is terminated and the screen is restored to its state before downgrade. If no such behavior is detected, the tablet computer is marked as being in a pre-sleep state. In the pre-sleep state, gyroscope data is continuously read, and it is identified whether there is a sudden change in motion data indicating that the device has been released from the user's hand; once the sudden change in motion data is identified, it is determined that the user has entered a sleep state. After determining that the user has entered a sleep state, the current time is recorded to update the sleep data, and a confirmation timer is started. If the gyroscope data does not change within the time set by the confirmation timer, a deep power-saving operation is performed, which includes at least terminating currently running non-essential programs and turning off the screen.

2. The tablet computer screen power-saving control method based on user behavior analysis according to claim 1, characterized in that, The reading of the user's sleep data specifically includes: Read the user-set bedtime from the local health data interface; Alternatively, the user's sleep history can be obtained through wearable devices paired with the tablet; Alternatively, it can be read from a user behavior prediction model trained locally on the tablet, which is generated by learning from long-term, multi-dimensional user habit data, including at least the timestamp of the last time the screen was turned off each day and the frequency of operation in the last hour before the screen was turned off.

3. The tablet computer screen power-saving control method based on user behavior analysis according to claim 1, characterized in that, The active correction behavior includes at least one or a combination of the following: Within a preset time period, the system detects that the user has increased the brightness by adjusting the brightness control via the touchscreen. After the user's screen degradation attempt was detected, continuous touch swipes or clicks exceeding a preset frequency threshold were triggered. The system detects the user's gaze returning to the screen using the front-facing camera.

4. The tablet computer screen power-saving control method based on user behavior analysis according to claim 1, characterized in that, The identification of whether a sudden change in motion data representing the release of the device occurs specifically includes: Calculate the mean square error of the gyroscope's three-axis angular velocity data within the sliding time window. If the mean square error exceeds a preset mutation threshold, it is determined that a mutation has occurred in the motion data. Alternatively, the real-time gyroscope data stream can be input into a trained lightweight neural network model. When the confidence level of the "drop / fall" event classification output by the model exceeds a preset threshold, the motion data mutation is determined to have occurred.

5. The tablet computer screen power-saving control method based on user behavior analysis according to claim 1, characterized in that, The specific method for performing the deep power-saving operation is as follows: First, simulate the lock screen key command to put the currently running program into a background suspension state; after the confirmation timer expires, clear the background suspension non-critical programs one by one, and finally turn off the screen.

6. The tablet computer screen power-saving control method based on user behavior analysis according to claim 1, characterized in that, In the screen degradation trial operation, the reduction in screen brightness and / or screen refresh rate is gradual. After the trial execution step is initiated, the system gradually adjusts the screen brightness and / or refresh rate to the target value in a step-by-step or continuous slow-down manner within a preset time. Prior to the sleep window acquisition step, an enable condition judgment step is also included: The current power supply mode and battery level of the tablet computer are detected. If the tablet computer is powered by an external power source or the battery level is higher than a preset safety threshold, the subsequent steps of the method will not be initiated.

7. A tablet computer screen power-saving control system based on user behavior analysis, characterized in that, include: Sleep data reading module: used to obtain the user's habitual sleep start time range and define it as the sleep prediction window; Trial control module: When the system time enters the sleep prediction window and the tablet computer is detected to be in user use state, actively reduce the screen brightness and / or screen refresh rate; Feedback monitoring module: Used to monitor the user's proactive corrective behavior in real time after the screen is downgraded. If no corrective behavior is detected, a pre-sleep state signal is triggered. Physical state confirmation module: connected to a gyroscope, used to analyze gyroscope data to identify sudden release after receiving the pre-sleep state signal, and generate a sleep confirmation signal when it is identified; Energy-saving execution and learning module: It is used to receive the sleep confirmation signal, record the time to update the user's sleep habits in the sleep data reading module, and perform deep power-saving operations such as turning off the screen and clearing background programs after a delay to confirm that there are no subsequent actions.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

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

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

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