A power consumption control method for one-screen multi-display

Abstract

The application discloses a power consumption control method for one-screen multi-display, and relates to the technical field of vehicle-mounted screen power consumption control, in particular to a power consumption control method for one-screen multi-display, which comprises the following steps: obtaining historical screen interaction data of a display screen, and performing grid division processing on the display screen; performing screen area classification processing on each screen grid, and performing area weight division to obtain screen area weight data; collecting current screen interaction data in real time, and performing interaction value analysis to obtain partition interaction value data; and dividing the priority of screen display partitions, and adjusting the display effect; the application is used to solve the problem that the existing vehicle-mounted screen power consumption control technology cannot obtain the demand priority of users for display partitions according to historical interaction information of users and display screens, and in combination with current interaction information of users and display screens, and then accurately reduce the power consumption of vehicle-mounted screens when the power consumption of one-screen multi-display vehicle-mounted screens is controlled.

Description

Technical Field

[0001] This invention relates to the field of power consumption control technology for vehicle screens, specifically a power consumption control method for multiple displays on a single screen. Background Technology

[0002] In-vehicle screen power consumption control technology refers to a comprehensive technical system that reduces screen energy consumption and improves energy utilization efficiency through various means such as hardware optimization, software algorithms, and scenario-based strategies, while ensuring the normal function and user experience of the in-vehicle screen. Its core objective is to reduce the screen's consumption of vehicle power, extend driving range, reduce energy loss, and ensure stable operation of the screen under extreme conditions.

[0003] Existing power consumption control technologies for in-vehicle screens with multiple displays often reduce power consumption by lowering the refresh rate and brightness of certain display zones, or by using a dark mode. However, these methods typically require manual or timed activation, or automatic activation based on environmental parameters. If a user is actively using a display zone and suddenly the display quality is reduced or dark mode is activated for power reasons, the user experience will inevitably suffer, such as decreased screen smoothness and visual clarity. Conversely, reducing power consumption based on inactive display zones would be problematic. The display effect of non-operational zones is prone to degrading the user's screen priority due to misjudging the user's screen needs, thus reducing the user experience. This is because inactivity does not mean that the user does not need it. For example, if a user is viewing a map interface and then tries to switch music on the music interface, the map interface's display effect will be reduced due to the short-term inactivity, affecting the user's acquisition of map information. Therefore, existing in-vehicle screen power consumption control technologies cannot accurately reduce the power consumption of in-vehicle screens with multiple displays by combining the user's historical interaction information with the display screen with the current interaction information to determine the user's priority of display zones. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. It obtains historical screen interaction data of a display screen and performs grid division processing on the display screen based on this data to obtain multiple display grids. Based on the historical screen interaction data, each screen grid undergoes screen area hierarchical processing and area weighting to obtain screen area weight data. Real-time acquisition of current screen interaction data of the display screen is performed, and interaction value analysis is conducted based on the screen area weight data to obtain partition interaction value data. The priority of screen display partitions is determined based on the partition interaction value data, and the display effect is controlled and adjusted. This addresses the problem that existing in-vehicle screen power consumption control technologies, when controlling the power consumption of multi-display in-vehicle screens, cannot accurately reduce the power consumption of in-vehicle screens by combining historical user interaction information with current interaction information with the display screen to determine the user's priority for display partitions.

[0005] To achieve the above objectives, this application provides a power consumption control method for multi-display on a single screen, comprising the following steps:

[0006] The historical screen interaction data of the display screen is obtained, and the display screen is divided into grids based on the historical screen interaction data to obtain multiple display grids;

[0007] Based on historical screen interaction data, each screen grid is processed to classify screen regions and then weighted to obtain screen region weight data.

[0008] Real-time acquisition of current screen interaction data of the display screen, and interaction value analysis based on screen area weight data to obtain partition interaction value data;

[0009] The screen display zones are prioritized based on the interactive value data of each zone, and the display effect is controlled and adjusted accordingly.

[0010] Further, acquiring historical screen interaction data of the display screen and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids includes the following sub-steps:

[0011] The entire display area of ​​the screen is designated as the first display area, and the coordinates of each pixel in the first display area are obtained.

[0012] For any pixel in the first display area, denoted as the first pixel, when the user clicks once at the location of the first pixel, or the user enters the delete character at the location of the first pixel, or the cursor stays at the location of the first pixel for more than k1, the interaction count of the first pixel is incremented by one, where k1 is the set duration;

[0013] Repeatedly obtain the interaction count of each pixel in the first display area within the first time length, and record the pixels with a non-zero interaction count as interactive pixels. After completion, obtain the historical screen interaction data, where the first time length is T1.

[0014] Furthermore, acquiring historical screen interaction data of the display screen and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids also includes the following sub-steps:

[0015] For any interactive pixel, denoted as the first interactive point, the interactive pixel closest to the first interactive point is denoted as the neighboring interactive point of the first interactive point, and the Euclidean distance from the first interactive point to the neighboring interactive point is calculated and denoted as the neighboring distance of the first interactive point.

[0016] Repeatedly obtain the adjacent distances of all interactive pixels and arrange them in ascending order, denoted as the adjacent distance sequence. Calculate the average of the first k2% of adjacent distances in the adjacent distance sequence, denoted as the first adjacent distance DA, where k2% is a set ratio.

[0017] Arrange the interaction counts of all interactive pixels in ascending order, and denote it as the interaction count sequence. Use a density clustering algorithm to divide the interaction count sequence into k3 clusters, and sort the clusters according to the size of the largest number of interaction counts contained in them. Obtain the k4 largest clusters, which are denoted as the high-frequency clusters, where k3 is the number of clusters and k4 is the set number.

[0018] For each high-frequency cluster, obtain the Euclidean distance between the two farthest interacting pixels within the cluster, and arrange them in order of size as the cluster diameter sequence. The median of the cluster diameter sequence is denoted as the second cluster distance DB.

[0019] Furthermore, acquiring historical screen interaction data of the display screen and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids also includes the following sub-steps:

[0020] The grid side length DC is calculated based on the first adjacent distance DA and the second clustering distance DB, where DC = q1 × DA + q2 × (DB / 3), q1 and q2 are the set weights, and q1 + q2 = 1;

[0021] Set the size of the grid to DC×DC. Use the grid to divide all screen display partitions within the first display area into multiple display grids, and denote any one of the display grids as the first grid area.

[0022] Furthermore, based on historical screen interaction data, each screen grid is processed into screen region hierarchical levels, and region weights are assigned to obtain screen region weight data, including the following sub-steps:

[0023] Get the total number of interactions of all interactive pixels in the first grid area within the first time length, and record it as the grid interaction number of the first grid area; repeatedly get the grid interaction number of all grid areas, and arrange them in descending order, and record them as the grid interaction sequence;

[0024] Calculate the average value of the grid interaction sequence, denoted as PA, and mark the display grids with a grid interaction number greater than or equal to k5×PA as active grids, where k5 is the set scaling factor;

[0025] If two active grids are within each other's 8-neighbor grids, they are considered adjacent and merged into a hotspot region. This process is repeated to assign all active grids to the corresponding hotspot region.

[0026] Furthermore, the process of hierarchically classifying each screen grid based on historical screen interaction data and assigning weights to each region to obtain screen region weight data includes the following sub-steps:

[0027] Let any hotspot area be designated as the first hotspot area, and obtain the average number of grid interactions of all active grids in the first hotspot area, denoted as PB;

[0028] The active grid with the largest number of grid interactions in the first hot spot area is designated as the central grid. K6 layers of active grids extend outward from the central grid and are designated as the central extension grids. The central grid and the central extension grids with a number of grid interactions greater than k7×PB are designated as core grids. Active grids in the first hot spot area that are not core grids are designated as transition grids. Here, k6 is the set number of layers and k7 is the set scaling factor.

[0029] Repeatedly acquire all core grids and transition grids within the first display area, and mark other display grids as edge grids.

[0030] Furthermore, the process of hierarchically classifying each screen grid based on historical screen interaction data and assigning weights to each region to obtain screen region weight data includes the following sub-steps:

[0031] Obtain the sum of the mesh interactions of all core meshes, the sum of the mesh interactions of all transition meshes, and the sum of the mesh interactions of all edge meshes, and denote them as H1, H2, and H3 in order, respectively; calculate the interaction ratio R1 of the core meshes, the interaction ratio R2 of the transition meshes, and the interaction ratio R3 of the edge meshes, where R1=H1 / H0, R2=H2 / H0, R3=H3 / H0, and H0=H1+H2+H3;

[0032] Set the initial weight of the edge to Ce, the initial weight of the transition to Be, and the initial weight of the core to Ae, where Be = min(H1 / H2, q3) × Ce, and Ae = min(H2 / H3, q4) × Be, where q3 and q4 are the set scaling factors;

[0033] Based on Ae:Be:Ce=R1:R2:R3, the specific Ae, Be and Ce are calculated and recorded in order as the basic weight V1 of the core grid, the basic weight V2 of the transition grid and the basic weight V3 of the edge grid.

[0034] Obtain the maximum number of mesh interactions in the core mesh, the maximum number of mesh interactions in the transition mesh, and the maximum number of mesh interactions in the edge mesh, respectively;

[0035] For the first grid region, calculate the ratio of the number of grid interactions in the first grid region to the number of interactions in the corresponding largest grid region, and denot it as the interaction ratio coefficient; then multiply the interaction ratio coefficient by the corresponding basic weight to obtain the grid-specific weight of the first grid region;

[0036] Repeatedly obtain the grid-specific weights of all display grids within the first display area, and then obtain the screen area weight data.

[0037] Furthermore, real-time acquisition of current screen interaction data and analysis of interaction value based on screen area weight data to obtain partitioned interaction value data includes the following sub-steps:

[0038] The number of grid interactions of all display grids in the first display area within the second time length is collected in real time and recorded as the current screen data, where the second time length is T2;

[0039] The second time length is evenly divided into k8 time sub-intervals, which are denoted as time sub-intervals 1-k8 in order of time from farthest to nearest. For any time sub-interval i, the corresponding time weight SQi is calculated, SQi=i / (1+2+……+k8).

[0040] Any screen display partition within the first display area is denoted as the first display partition, and any display grid within the first display partition is denoted as the first partition grid.

[0041] Furthermore, the real-time collection of current screen interaction data and the analysis of interaction value based on screen area weight data to obtain partitioned interaction value data also include the following sub-steps:

[0042] Based on the current screen data, obtain the number of grid interactions of the first partition grid in time interval i, denoted as HDi. Based on the grid-specific weight of the first partition grid and the corresponding time weight, calculate the interaction value FH of the first partition grid in time sub-interval i, where FH=SQi×WQ×HDi, and WQ is the grid-specific weight of the first partition grid.

[0043] Repeatedly calculate the interaction value of the first partition grid in all time sub-intervals and sum them to obtain the interaction value of the first partition grid in the second time length, which is denoted as the grid interaction value;

[0044] Obtain the grid interaction value of all display grids within the first display partition, and record it as the grid interaction value data of the first display partition. Repeat this process to obtain the grid interaction value data of all screen display partitions, thus obtaining the partition interaction value data.

[0045] Furthermore, prioritizing screen display zones based on zone interaction value data and controlling and adjusting the display effect includes the following sub-steps:

[0046] The summation of the grid interaction values ​​of all display grids within the first display partition is denoted as the real-time interaction value SH of the first display partition.

[0047] Sort all display grids in the first display partition from largest to smallest according to their specific grid weights, and record the top k9% of grids as high-weight grids. Calculate the sum of the grid interaction values ​​of all high-weight grids, and record it as the core interaction value XH, where k9 is the set ratio coefficient.

[0048] Calculate the value concentration HE based on SH and XH, and calculate the partition priority YE of the first display partition, where HE = XH / SH, YE = SH × (1 + HE).

[0049] Repeatedly obtain the partition priority of all screen display partitions and sort them from largest to smallest. Record the screen display partition corresponding to the smallest 50% partition priority as the secondary display partition, reduce the refresh rate of the secondary display partition, and put the secondary display partition into dark display mode.

[0050] The beneficial effects of this invention are as follows: This invention acquires historical screen interaction data of the display screen and performs grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids; it performs screen area hierarchical processing on each screen grid based on the historical screen interaction data and performs area weight division to obtain screen area weight data; it collects the current screen interaction data of the display screen in real time and performs interaction value analysis based on the screen area weight data to obtain partition interaction value data; it divides the priority of screen display partitions based on the partition interaction value data and controls and adjusts the display effect; when controlling the power consumption of a multi-display vehicle screen, it can obtain the user's demand priority for display partitions based on the user's historical interaction information with the display screen and combined with the current interaction information with the display screen, thereby accurately reducing the power consumption of the vehicle screen.

[0051] This invention utilizes historical screen interaction data to dynamically determine the optimal grid side length by calculating the Euclidean distance between interactive pixels and the median cluster diameter of high-frequency clusters. Its advantage lies in ensuring that the divided grid satisfies both high-density interaction areas and avoids wasting computational resources in low-interaction areas, thus avoiding the subjectivity of manual settings and balancing the needs for finer segmentation in different areas. Active grids are merged into hotspot areas, and then the grids are displayed in categories. A basic weight is calculated based on the proportion of the three types of grids in the total interaction, ultimately obtaining a specific weight for each grid. This allows the assigned weights to accurately match the user's actual usage habits, providing a basis for subsequent power consumption control that aligns with user behavior, and precisely reducing power consumption in unimportant areas. Attached Figure Description

[0052] Figure 1 This is a flowchart of the steps of the method of the present invention;

[0053] Figure 2 This is a flowchart of the mesh generation process of the present invention;

[0054] Figure 3 This is a flowchart of the screen area hierarchical processing of the present invention;

[0055] Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Example 1, please refer to Figure 1As shown, this application provides a power consumption control method for multiple displays on a single screen, including the following steps:

[0058] Step S1 involves acquiring historical screen interaction data of the display screen and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids; Step S1 includes the following sub-steps:

[0059] Step S101: Record all display areas of the display screen as the first display area, and obtain the coordinates of each pixel in the first display area;

[0060] Step S102: For any pixel in the first display area, denoted as the first pixel, when the user clicks once at the location of the first pixel, or the user enters the delete character at the location of the first pixel, or the cursor stays at the location of the first pixel for more than k1, the interaction count of the first pixel is incremented by one. If the display screen does not have a cursor similar to a mouse during use, this step can be ignored. Here, k1 is the set duration. In this embodiment, k1 is 10 seconds.

[0061] Step S103: Repeatedly obtain the number of interactions for each pixel in the first display area within the first time length, and record the pixels with non-zero interaction counts as interactive pixels. After completion, historical screen interaction data is obtained, where the first time length is T1; in this embodiment, T1 = 30 days.

[0062] For step S104, please refer to... Figure 2 As shown, for any interactive pixel, it is denoted as the first interactive point. The interactive pixel closest to the first interactive point is denoted as the neighboring interactive point of the first interactive point. The Euclidean distance from the first interactive point to the neighboring interactive point is calculated and denoted as the neighboring distance of the first interactive point.

[0063] Step S105: Repeatedly obtain the adjacent distances of all interactive pixels and arrange them in ascending order, denoted as the adjacent distance sequence. Calculate the average value of the first k2% of the adjacent distances in the adjacent distance sequence, denoted as the first adjacent distance DA, where k2% is a set percentage; in this embodiment, k2% = 90%; the first adjacent distance DA reflects the "average dispersion" of interactive pixels in space. The smaller the distance, the denser the interactive pixels are, and the smaller the grid needs to be divided.

[0064] Step S106: Arrange the interaction counts of all interactive pixels in ascending order, and denote it as the interaction count sequence; use a density clustering algorithm to divide the interaction count sequence into k3 clusters, and sort the clusters according to the largest number of interaction counts contained therein, obtaining the largest k4 clusters, which are denoted as high-frequency clusters, where k3 is the number of clusters and k4 is the set number; k3 can be set by the density clustering algorithm itself, and in this embodiment, k4 = 0.3 × k3; the high-frequency clusters represent the areas most frequently operated by the user;

[0065] Step S107: For each high-frequency cluster, obtain the Euclidean distance between the two farthest interacting pixels in the cluster, and arrange them in order of size as the cluster diameter sequence. The median of the cluster diameter sequence is recorded as the second cluster distance DB. The second cluster distance reflects the "spatial range" of the core operation area. The smaller the diameter, the more concentrated the high-frequency interaction is, and the smaller the grid is needed to capture details.

[0066] Step S108: Calculate the grid side length DC based on the first adjacent distance DA and the second clustering distance DB, where DC = q1 × DA + q2 × (DB / 3), q1 and q2 are the set weights, q1 + q2 = 1; in this embodiment, q1 = q2 = 0.5; DB / 3 is because 1 / 3 of the cluster diameter is approximately equal to the "detail capture granularity" within the cluster, and can also be adjusted according to the actual application scenario;

[0067] DC calculates a small grid when interactions are dense and automatically adapts to a larger grid when interactions are sparse. It can find a balance between dense and sparse areas without manually setting initial values, avoiding the subjectivity of manual setting and balancing the interaction fineness requirements of different areas. The grid size matches the "natural distribution scale of global interaction points" - neither too small to cause redundant calculations in sparse areas, nor too large to cause loss of details in dense areas.

[0068] Step S109: Set the size of the grid to DC×DC, and use the grid to divide all screen display partitions in the first display area into multiple display grids, and record any one of the display grids as the first grid area;

[0069] In the specific implementation process, the reason for dividing the first display area into grids is that if subsequent weight calculations, priority sorting, and real-time control are performed directly on a pixel-by-pixel basis, it would be necessary to manage data from millions or even tens of millions of pixels, resulting in extremely high computational and storage costs. After gridding, it is only necessary to maintain statistical data for each DC×DC grid as a whole, which significantly reduces the number of units that need to be processed, significantly improves computational efficiency, and reduces computational power consumption. Furthermore, the grid size is adaptively calculated based on historical screen interaction data, which can both finely cover high-density interaction areas and avoid over-division in sparse areas. By reasonably selecting DCs, the optimal balance between power consumption and performance can be achieved while ensuring user experience.

[0070] Step S2 involves performing screen region hierarchical processing on each screen grid based on historical screen interaction data, and then dividing the region into weights to obtain screen region weight data. Step S2 includes the following sub-steps:

[0071] Step S201: Obtain the sum of the number of interactions of all interactive pixels in the first grid area within the first time length, and record it as the grid interaction number of the first grid area; repeatedly obtain the grid interaction number of all grid areas, and arrange them in descending order, and record them as the grid interaction sequence;

[0072] Step S202: Calculate the average value of the grid interaction sequence, denoted as PA. Mark the displayed grids with a grid interaction number greater than or equal to k5×PA as active grids, where k5 is a set scaling factor; in this embodiment, k5=1.3; only focus on grids with high interaction numbers to reduce subsequent computational complexity;

[0073] Step S203: If two active grids are within each other's 8-neighbor grids, they are considered adjacent and merged into a hotspot region. Repeat this process to assign all active grids to the corresponding hotspot region. Aggregate the scattered high-interaction grids according to spatial connectivity to cover the areas where user operations are most frequent and concentrated.

[0074] For step S204, please refer to... Figure 3 As shown, any hotspot area is designated as the first hotspot area, and the average number of grid interactions among all active grids in the first hotspot area is obtained and denoted as PB.

[0075] Step S205: The active grid with the largest number of grid interactions in the first hotspot area is designated as the central grid. K6 layers of active grids extend outward from the central grid, designated as the central extension grids. The central grid and the central extension grids with a grid interaction number greater than k7×PB are designated as core grids. Active grids in the first hotspot area that are not core grids are designated as transition grids. Here, k6 is the set number of layers, and k7 is the set scaling factor. In this embodiment, k6=1, k7=0.8.

[0076] Step S206: Repeatedly acquire all core grids and transition grids within the first display area, and mark other display grids as edge grids; by setting different levels for the display grids, the user's usage habits of screen partitions are more finely divided, providing a classification basis for subsequent weight assignment; core grids are areas where users interact most frequently, such as around the document editing cursor and the main function button area of ​​the software; transition grids are areas where users interact relatively frequently, such as the side toolbar and menu drop-down area of ​​the software; edge grids are areas where users interact less or not at all, such as blank areas on the desktop;

[0077] Step S207: Obtain the sum of the mesh interactions of all core meshes, the sum of the mesh interactions of all transition meshes, and the sum of the mesh interactions of all edge meshes, and denote them as H1, H2, and H3 in order; calculate the interaction ratio R1 of the core meshes, the interaction ratio R2 of the transition meshes, and the interaction ratio R3 of the edge meshes, where R1=H1 / H0, R2=H2 / H0, R3=H3 / H0, and H0=H1+H2+H3;

[0078] Step S208: Set the initial weight of the edge to Ce, the initial weight of the transition to Be, and the initial weight of the core to Ae, where Be = min(H1 / H2, q3) × Ce, and Ae = min(H2 / H3, q4) × Be; where q3 and q4 are set proportional coefficients. In this embodiment, Ce = 0.5, q3 = q4 = 1.5. To avoid the interaction of the transition mesh accidentally increasing and overtaking the core mesh, a fixed hierarchical multiple relationship needs to be set. At the same time, to avoid H1 / H3 and H1 / H2 being too large and causing abnormal weights, q3 and q4 need to be set as upper limits.

[0079] Step S209: Based on Ae:Be:Ce=R1:R2:R3, calculate the specific Ae, Be, and Ce, and record them in order as the basic weight V1 of the core grid, the basic weight V2 of the transition grid, and the basic weight V3 of the edge grid. The basic weight is directly related to the total interaction of each level of grid. The more interaction, the higher the basic weight, which is more in line with the user's actual operation focus.

[0080] Step S210: Obtain the maximum number of mesh interactions in the core mesh, the maximum number of mesh interactions in the transition mesh, and the maximum number of mesh interactions in the edge mesh, respectively;

[0081] Step S211: For the first grid area, calculate the ratio of the number of grid interactions in the first grid area to the number of interactions in the corresponding largest grid area, denoted as the interaction ratio coefficient; and multiply the interaction ratio coefficient by the corresponding basic weight to obtain the grid-specific weight of the first grid area; for example, if the first grid area is the core grid, the largest number of grid interactions in the core grid is 500, the number of grid interactions in the first grid area is 400, and the basic weight of the core grid is V1=1.2, then the interaction ratio coefficient of the first grid area = 400 / 500 = 0.8, and the grid-specific weight of the first grid area = 1.2 × 0.8 = 0.96; where the interaction ratio coefficient reflects the activity level of the grid among similar grids; the basic weight reflects the importance of this type of grid to the user.

[0082] Step S212: Repeatedly obtain the grid-specific weights of all display grids within the first display area, and obtain the screen area weight data after completion;

[0083] In the actual implementation process, the information and functions carried by different display zones of the vehicle screen are very different. For example, the navigation zone and the entertainment zone. If the priority is determined by subjective judgment alone, it is easy to make control adjustment errors. However, by calculating the specific weight of each grid, the ambiguous importance and secondary importance can be transformed into precise values, which facilitates subsequent comparison. This allows for the corresponding adjustment of the less important display zones, thereby reducing power consumption.

[0084] Step S3 involves real-time acquisition of current screen interaction data and interactive value analysis based on screen area weight data to obtain partitioned interactive value data. Step S3 includes the following sub-steps:

[0085] Step S301: Real-time collection of the number of grid interactions of all display grids in the first display area within the second time length, recorded as the current screen data, where the second time length is T2; in this embodiment, T2 = 1 hour, that is, collecting the current screen data of the most recent 1 hour;

[0086] Step S302: Divide the second time length evenly into k8 time sub-intervals, and denote them as time sub-intervals 1-k8 in order of time from farthest to nearest; For any time sub-interval i, calculate the corresponding time weight SQi, SQi=i / (1+2+……+k8); In this embodiment, k8=12; The more recent the interaction, the higher the weight, which conforms to the immediacy characteristics of human-computer interaction.

[0087] Step S303: For any screen display partition in the first display area, denoted as the first display partition, and any display grid within the first display partition, denoted as the first partition grid;

[0088] Step S304: Based on the current screen data, obtain the number of grid interactions of the first partition grid within time interval i, denoted as HDi. Calculate the interaction value FH of the first partition grid within time sub-interval i based on the grid-specific weight and corresponding time weight of the first partition grid, where FH = SQi × WQ × HDi, and WQ is the grid-specific weight of the first partition grid; for example, if WQ = 0.96, HD8 = 16, and SQ8 = 0.10, then the interaction value FH of the first partition grid within time sub-interval i = 0.10 × 0.96 × 16 = 1.536.

[0089] Step S305: Repeatedly calculate the interaction value of the first partition grid in all time sub-intervals and sum them to obtain the interaction value of the first partition grid in the second time length, which is denoted as the grid interaction value.

[0090] Step S306: Obtain the grid interaction value of all display grids in the first display partition, and record it as the grid interaction value data of the first display partition. Repeat the process of obtaining the grid interaction value data of all screen display partitions to obtain the partition interaction value data.

[0091] In practical implementation, the grid interaction value of the display grid is the core indicator that measures the urgency and necessity of a display grid being actively operated, relied upon, or requiring immediate response from users within the current time window; it is essentially a quantitative description of the intensity of the user's real-time interaction needs with the grid.

[0092] Step S4 involves prioritizing screen display zones based on the zone interaction value data and controlling and adjusting the display effect; Step S4 includes the following sub-steps:

[0093] Step S401: Sum the grid interaction values ​​of all display grids in the first display partition and record it as the real-time interaction value SH of the first display partition;

[0094] Step S402: Sort all display grids in the first display partition from largest to smallest according to their specific grid weights, and record the top k9% of grids as high-weight grids. Calculate the sum of the grid interaction values ​​of all high-weight grids, and record it as the core interaction value XH, where k9 is a set proportional coefficient; in this embodiment, k9=0.3, and the proportional coefficient can be flexibly adjusted.

[0095] Step S403: Calculate the value concentration HE based on SH and XH, and calculate the partition priority YE of the first display partition, where HE = XH / SH, YE = SH × (1 + HE); the value concentration is used to measure whether the interaction value within a partition is concentrated in the high-weight grid. The more concentrated it is, the higher the interaction quality of the partition; that is, for two partitions with the same interaction value, the one with the higher value concentration will get a higher priority because its interaction has a higher "effective value".

[0096] Step S404: Repeatedly obtain the partition priority of all screen display partitions, and sort them in descending order. Record the screen display partition corresponding to the lowest 50% partition priority as the secondary display partition, reduce the refresh rate of the secondary display partition, and put the secondary display partition into dark display mode.

[0097] In practice, dark mode is a display mode with a dark background, usually black or dark gray, paired with light-colored text as the main visual style, in contrast to the traditional light mode. For OLED and AMOLED screens, each pixel of these screens is self-emissive. Black pixels can be completely turned off, while white pixels need to emit light. The higher the brightness, the greater the power consumption. Therefore, in dark mode, pixels in large black areas stop working, directly reducing the total light emission of the screen, thereby significantly reducing power consumption.

[0098] Example 2, please refer to Figure 4 As shown, Figure 4 A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps similar to those in a power consumption control method for multi-display devices on a single screen, to achieve the following functions: acquiring historical screen interaction data of the display screen, and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids; performing screen region hierarchical processing on each screen grid based on the historical screen interaction data, and performing region weight division to obtain screen region weight data; collecting current screen interaction data of the display screen in real time, and performing interaction value analysis based on the screen region weight data to obtain partition interaction value data; prioritizing screen display partitions based on the partition interaction value data, and controlling and adjusting the display effect.

[0099] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0100] Example 3: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of a power consumption control method for multiple displays on a single screen to achieve the following functions: acquiring historical screen interaction data of the display screen, and performing grid division processing on the display screen based on the historical screen interaction data to obtain multiple display grids; performing screen area hierarchical processing on each screen grid based on the historical screen interaction data, and performing area weight division to obtain screen area weight data; collecting the current screen interaction data of the display screen in real time, and performing interaction value analysis based on the screen area weight data to obtain partition interaction value data; dividing the priority of screen display partitions based on the partition interaction value data, and controlling and adjusting the display effect.

[0101] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0102] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0103] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A power consumption control method for one-screen multi-display, characterized by, The method comprises the following steps: Obtain historical screen interaction data of the display screen, and perform grid division processing on the display screen according to the historical screen interaction data to obtain a plurality of display grids; Perform screen area classification processing on each screen grid based on the historical screen interaction data, and perform area weight division to obtain screen area weight data; Real-time collect current screen interaction data of the display screen, and perform interaction value analysis according to the screen area weight data to obtain partition interaction value data; Divide the priority of the screen display partition according to the partition interaction value data, and control and adjust the display effect; Obtain historical screen interaction data of the display screen, and perform grid division processing on the display screen according to the historical screen interaction data to obtain a plurality of display grids, comprising the following sub-steps: Record all display areas of the display screen as first display areas, and obtain the coordinates of each pixel point of the first display areas; For any one pixel point of the first display areas, record it as a first pixel point, when the user clicks once at the position of the first pixel point, or the user inputs a delete character at the position of the first pixel point, or the time of indicating the cursor staying at the position of the first pixel point exceeds k1, then the interaction times of the first pixel point is added by one, wherein k1 is a set time length; Repeat the obtaining of the interaction times of each pixel point of the first display areas within a first time length, and record the pixel points with the interaction times of 0 as interactive pixel points, and the historical screen interaction data is obtained after completion, wherein the first time length is T1.

2. The power consumption control method of one-screen multi-display according to claim 1, wherein, Obtain historical screen interaction data of the display screen, and perform grid division processing on the display screen according to the historical screen interaction data to obtain a plurality of display grids, comprising the following sub-steps: For any one interactive pixel point, record it as a first interactive point, record the interactive pixel point closest to the first interactive point as the adjacent interactive point of the first interactive point, calculate the Euclidean distance from the first interactive point to the adjacent interactive point, and record it as the adjacent distance of the first interactive point; Repeat the obtaining of the adjacent distances of all interactive pixel points, and arrange them in ascending order to record them as an adjacent distance sequence, calculate the average value of the adjacent distances of the first k2% of the adjacent distance sequence, and record it as the first adjacent distance DA, wherein k2% is a set proportion; Arrange the interaction times of all interactive pixel points in ascending order to record them as an interaction time sequence; divide the interaction time sequence into k3 time clusters by using a density clustering algorithm, sort the time clusters according to the size of the maximum interaction times contained, obtain the maximum k4 time clusters, and record them as high-frequency time clusters, wherein k3 is the number of clusters divided, and k4 is a set number; For each high-frequency time cluster, obtain the Euclidean distance of the two farthest interactive pixel points in the cluster, and arrange them in size to record them as a clustering diameter sequence, and record the median of the clustering diameter sequence as a second clustering distance DB.

3. The power consumption control method of one-screen multi-display according to claim 2, wherein, Obtain historical screen interaction data of the display screen, and perform grid division processing on the display screen according to the historical screen interaction data to obtain a plurality of display grids, comprising the following sub-steps: Calculate the grid length DC according to the first adjacent distance DA and the second clustering distance DB, wherein DC=q1×DA+q2×(DB / 3), q1 and q2 are set weights, and q1+q2=1; Set the size of the divided grid as DC×DC, divide all the screen display partitions in the first display area into a plurality of display grids by using the divided grid, and mark any one display grid as a first grid area.

4. The power consumption control method of one-screen multi-display according to claim 3, wherein, Screen area classification processing is performed on each screen grid based on historical screen interaction data, and area weight division is performed to obtain screen area weight data, including the following sub-steps: Obtain the total number of interactions of all interactive pixel points in the first grid area within the first time length, and mark it as the grid interaction number of the first grid area; repeat the grid interaction number of all grid areas, and arrange them in descending order, and mark them as a grid interaction sequence; Calculate the average value of the grid interaction sequence, mark it as PA, and mark the display grid with a grid interaction number greater than or equal to k5×PA as an active grid, wherein k5 is a set proportion coefficient; If two active grids are in each other's 8-neighborhood grid, it is judged to be adjacent, and then merged into one hotspot area, and all active grids are repeatedly classified into corresponding hotspot areas.

5. The power consumption control method of one-screen multi-display according to claim 4, wherein, Screen area classification processing is performed on each screen grid based on historical screen interaction data, and area weight division is performed to obtain screen area weight data, including the following sub-steps: Mark any one hotspot area as a first hotspot area, and obtain the average value of the grid interaction number of all active grids in the first hotspot area, and mark it as PB; Mark the active grid with the largest grid interaction number in the first hotspot area as a center grid, extend k6 layers of active grids outward from the center grid, mark them as a center extension grid, and mark the center grid and the center extension grid with a grid interaction number greater than k7×PB as a core grid; Mark the active grid in the first hotspot area that is not a core grid as a transition grid, wherein k6 is a set number of layers, and k7 is a set proportion coefficient; Repeat the process of obtaining all core grids and transition grids in the first display area, and mark other display grids as edge grids.

6. The power consumption control method of one-screen multi-display according to claim 5, wherein, Screen area classification processing is performed on each screen grid based on historical screen interaction data, and area weight division is performed to obtain screen area weight data, including the following sub-steps: Obtain the sum of the grid interaction numbers of all core grids, the sum of the grid interaction numbers of all transition grids, and the sum of the grid interaction numbers of all edge grids, and mark them as H1, H2, and H3 in order, respectively; calculate the interaction proportion R1 of the core grid, the interaction proportion R2 of the transition grid, and the interaction proportion R3 of the edge grid, wherein R1=H1 / H0, R2=H2 / H0, and R3=H3 / H0, and H0=H1+H2+H3; Set the edge initial weight as Ce, the transition initial weight as Be, and the core initial weight as Ae, wherein Be=min(H1 / H2, q3)×Ce, and Ae=min(H2 / H3, q4)×Be, wherein q3 and q4 are set proportion coefficients; According to Ae: Be: Ce = R1: R2: R3, the specific Ae, Be and Ce are calculated, and are sequentially recorded as the basic weight V1 of the core grid, the basic weight V2 of the transition grid and the basic weight V3 of the edge grid respectively; The maximum grid interaction number in the core grid, the maximum grid interaction number in the transition grid and the maximum grid interaction number in the edge grid are respectively obtained; For the first grid area, the proportion of the grid interaction number of the first grid area to the corresponding maximum grid interaction number is calculated, which is recorded as an interaction proportion coefficient; and the interaction proportion coefficient is multiplied by the corresponding basic weight to obtain the grid specific weight of the first grid area; The grid specific weights of all display grids in the first display area are repeatedly obtained, and the screen area weight data is obtained after completion.

7. The power consumption control method of one-screen multi-display according to claim 6, wherein, Real-time acquisition of current screen interaction data of the display screen, and interaction value analysis according to the screen area weight data to obtain partition interaction value data, including the following sub-steps: Real-time acquisition of the grid interaction number of all display grids in the first display area within a second time length, recorded as current screen data, wherein the second time length is T2; The second time length is evenly divided into k8 time subintervals, which are sequentially recorded as time subintervals 1-k8 from far to near; for any one time subinterval i, the corresponding time weight SQi is calculated, SQi = i / (1+2+…+k8); Real-time acquisition of current screen interaction data of the display screen, and interaction value analysis according to the screen area weight data to obtain partition interaction value data, including the following sub-steps:

8. The power consumption control method of one-screen multi-display according to claim 7, wherein, According to the current screen data, the grid interaction number of the first partition grid in the time interval i is obtained, recorded as HDi, and the interaction value of the first partition grid in the time subinterval i is calculated according to the grid specific weight of the first partition grid and the corresponding time weight, FH, wherein FH = SQi × WQ × HDi, WQ is the grid specific weight of the first partition grid; The interaction value of the first partition grid in all time subintervals is repeatedly calculated and summed to obtain the interaction value of the first partition grid within the second time length, recorded as the grid interaction value; The grid interaction values of all display grids in the first display partition are obtained, recorded as the grid interaction value data of the first display partition, and the grid interaction value data of all screen display partitions is repeatedly obtained to obtain the partition interaction value data. According to the partition interaction value data, the priority of the screen display partition is divided, and the display effect is controlled and adjusted, including the following sub-steps:

9. The power consumption control method of one-screen multi-display according to claim 8, wherein, The sum of the grid interaction values of all display grids in the first display partition is calculated, recorded as the immediate interaction value SH of the first display partition; All display grids in the first display partition are sorted according to the grid specific weight from large to small, and the first k9% of the grids are recorded as high weight grids, and the sum of the grid interaction values of all high weight grids is calculated, recorded as the core interaction value XH, wherein k9 is a set proportion coefficient; ​ According to SH and XH, a value concentration HE is calculated, and a partition priority YE of the first display partition is calculated, wherein HE=XH / SH, and YE=SH×(1+HE); The partition priority of all screen display partitions is repeatedly acquired, and is arranged from large to small, and the screen display partition corresponding to the smallest 50% of the partition priority is recorded as a secondary display partition, the refresh rate of the secondary display partition is reduced, and the secondary display partition is made to enter a dark display mode.

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