Temperature control method and device and electronic equipment

Abstract

The invention discloses a temperature control method and device and electronic equipment, and belongs to the technical field of electronic equipment. The temperature control method comprises the steps of predicting first temperature change trend data and first load change trend data of a processor in the electronic equipment in a future first duration through a prediction unit based on currently collected temperature related data and historically collected temperature related data; determining a target temperature control strategy based on currently acquired temperature related data, the first temperature change trend data and the first load change trend data through a decision unit, and sending an execution instruction to a target object indicated by the target temperature control strategy; wherein the temperature related data comprises task parameters of services executed by the electronic equipment, and temperature data and load data of the processor; the execution instruction is used for indicating the target object to execute the target temperature control strategy.

Description

Technical Field

[0001] This application belongs to the field of electronic equipment technology, specifically relating to a temperature control method, device, and electronic equipment. Background Technology

[0002] With the rapid development of mobile communication technology, the imaging capabilities of electronic devices are becoming increasingly enhanced, supporting 4K, 8K, and even higher-resolution video recording. However, recording high-resolution, high-frame-rate video requires continuous high-intensity computation from components such as the contact image sensor (CIS), central processing unit (CPU), image signal processor (ISP), and encoder, which generates enormous computational power consumption, which is converted into heat energy, causing the electronic device to overheat.

[0003] In related technologies, the temperature control strategy adopted when electronic devices overheat is as follows: the temperature is monitored in real time by a temperature sensor installed on the electronic device. When the temperature exceeds a preset safety threshold, the electronic device triggers operations such as frequency reduction, reduction of recording specifications, or direct interruption of the recording process to protect hardware safety.

[0004] While the aforementioned temperature control strategies can reduce the temperature of electronic devices, they can affect normal recording, leading to reduced video quality or even recording interruption, thus affecting the electronic devices' ability to perform tasks. Summary of the Invention

[0005] The purpose of this application is to provide a temperature control method, device, and electronic device that can control the temperature of the electronic device without affecting task execution.

[0006] In a first aspect, embodiments of this application provide a temperature control method applied to an electronic device. The method includes: using a prediction unit to predict, based on currently collected temperature-related data and historically collected temperature-related data, a first temperature change trend and a first load change trend of the processor in the electronic device within a future first time period; using a decision unit to determine a target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and sending an execution instruction to the target object indicated by the target temperature control strategy; wherein the temperature-related data includes task parameters of the task executed by the electronic device, as well as the processor's temperature data and load data; the execution instruction is used to instruct the target object to execute the target temperature control strategy.

[0007] Secondly, embodiments of this application provide a temperature control device, comprising a prediction unit and a decision unit. The prediction unit is configured to predict, based on currently acquired temperature-related data and historically acquired temperature-related data, a first temperature change trend and a first load change trend of the processor in an electronic device within a future first time period. The decision unit is configured to determine a target temperature control strategy based on the currently acquired temperature-related data, the first temperature change trend data, and the first load change trend data, and send an execution instruction to the target object indicated by the target temperature control strategy. The aforementioned temperature-related data includes task parameters of the task performed by the electronic device, as well as the processor's temperature data and load data; the aforementioned execution instruction is used to instruct the target object to execute the target temperature control strategy.

[0008] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores a program or instructions executable on the processor, and the program or instructions, when executed by the processor, implement the steps of the temperature control method as described in the first aspect.

[0009] Fourthly, embodiments of this application provide a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the temperature control method as described in the first aspect.

[0010] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the temperature control method as described in the first aspect.

[0011] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the temperature control method as described in the first aspect.

[0012] In this embodiment, a prediction unit predicts the first temperature change trend data and the first load change trend data of the processor in the electronic device within a future first time period based on currently collected temperature-related data and historically collected temperature-related data; a decision unit determines a target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and sends an execution instruction to the target object indicated by the target temperature control strategy; wherein, the temperature-related data includes the task parameters of the task executed by the electronic device, as well as the temperature data and load data of the processor; the execution instruction is used to instruct the target object to execute the target temperature control strategy. Therefore, this solution, through its prediction unit, uses currently collected temperature-related data and historically collected temperature-related data to predict future power consumption and temperature changes of electronic devices under specific task parameters. Based on the prediction results, it proactively implements temperature control strategies to control the temperature, achieving a shift from "passive response" to "active prediction." Compared to cooling down the electronic device only after it has overheated, this solution can proactively control the temperature of the electronic device by implementing temperature control strategies when overheating is predicted, reducing the occurrence of overheating. It also eliminates the need for temperature control through frequency reduction, lowering recording specifications, or directly interrupting the recording process, thus controlling the temperature of the electronic device without affecting task execution. Attached Figure Description

[0013] Figure 1 This is one of the flowcharts illustrating the temperature control method provided in the embodiments of this application;

[0014] Figure 2 This is a second schematic flowchart of the temperature control method provided in the embodiments of this application;

[0015] Figure 3 This is the third schematic flowchart of the temperature control method provided in the embodiments of this application;

[0016] Figure 4 This is a schematic diagram of the temperature control system provided in the embodiments of this application;

[0017] Figure 5 This is a schematic diagram of the temperature control device provided in the embodiments of this application;

[0018] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application;

[0019] Figure 7 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0021] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0022] The terms "at least one," "at least one of," etc., used in the specification and claims of this application refer to any one, any two, or a combination of two or more of the included items. For example, at least one of a, b, and c can mean: "a," "b," "c," "a and b," "a and c," "b and c," and "a, b, and c," where a, b, and c can be single or multiple. Similarly, "at least two" refers to two or more items, and its meaning is similar to that of "at least one."

[0023] The temperature control method, device, electronic device, storage medium, and program product provided in this application will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0024] The temperature control method provided in this application can be applied to any scenario that may cause electronic devices to overheat, such as taking photos, recording videos, or playing games.

[0025] Taking video recording as an example, currently, the main heat dissipation methods for electronic devices rely on passive heat dissipation technologies, such as using graphene heat dissipation films and heat spreaders to conduct heat from the heat source to the device body and dissipate it into the environment. In addition, the temperature control strategies of electronic device systems are mostly passive response mechanisms: temperature sensors distributed throughout the device body monitor the temperature in real time, and once the temperature exceeds a preset safety threshold, the system will trigger frequency reduction, reduce recording specifications, or directly interrupt the recording process to protect hardware safety.

[0026] However, this method only takes action when the temperature has reached or is close to the safe threshold, and cannot cope with the thermal shock generated by high-specification video recording. This leads to unpredictable interruptions in video recording, making it a "remedial" measure with a lag in response. Furthermore, the forced recording degradation or interruption is very abrupt, severely disrupting the user's creative workflow, especially when shooting important scenes, which may lead to irreparable regrets. In addition, users cannot predict the device's continuous recording time, resulting in a poor user experience. In addition, to prevent the device from overheating, device manufacturers usually adopt conservative solutions in chip scheduling and temperature control strategies, which prevents the device's hardware potential from being continuously released to its maximum extent within a safe range, meaning that the device's performance is not fully utilized. Moreover, the heat dissipation capacity of purely passive cooling methods has a physical limit, and the heat dissipation efficiency is low. It is already inadequate when facing continuous high-load computing scenarios, which restricts the further improvement of the video recording performance of electronic devices.

[0027] To address this, this application provides a temperature control method. This method uses a prediction unit to predict future power consumption and temperature changes of an electronic device under specific task parameters, based on currently collected temperature-related data and historically collected temperature-related data. Based on the prediction results, a temperature control strategy is implemented in advance to control the temperature, achieving a shift from "passive response" to "active prediction." Compared to cooling down the electronic device only after it has overheated, this solution can proactively control the temperature of the electronic device by implementing a temperature control strategy when overheating is predicted. This reduces the occurrence of overheating and eliminates the need for temperature control through frequency reduction, lowering recording specifications, or directly interrupting the recording process. Thus, temperature control of the electronic device is achieved without affecting video recording.

[0028] The temperature control method provided in this application can be executed by a temperature control device. Exemplarily, the temperature control device can be an electronic device, or a functional component or entity within that electronic device. The following will use an electronic device as an example to illustrate the temperature control method provided in this application.

[0029] Figure 1 This is a schematic flowchart of the temperature control method provided in the embodiments of this application, as shown below. Figure 1 As shown, the temperature control method provided in this application embodiment may include the following steps 101 and 102.

[0030] Step 101: The electronic device, through the prediction unit, predicts the first temperature change trend data and the first load change trend data of the processor in the electronic device within the first time period in the future, based on the currently collected temperature-related data and the historically collected temperature-related data.

[0031] In some embodiments of this application, the prediction unit may be a hardware unit in an electronic device, such as a prediction engine; or, the prediction unit may be a software platform deployed in an electronic device or a virtual module in a software platform.

[0032] In some embodiments of this application, the temperature-related data may include task parameters of the tasks performed by the electronic device, as well as temperature data and load data of the processor.

[0033] In some embodiments of this application, the processor may include at least one of the following: a system on chip (SOC) or an image sensor (CIS).

[0034] In some embodiments of this application, the SOC described above may include at least one of the following: CPU, Graphics Processing Unit (GPU), and ISP.

[0035] In some embodiments of this application, the load data may include power consumption, or power consumption and operating frequency.

[0036] In some embodiments of this application, the task performed by the electronic device can be a video recording task, and the task parameters can be recording parameters during video recording.

[0037] In some embodiments of this application, the recording parameters may include at least one of the following: resolution, frame rate, encoding format, and special effects algorithm on / off status.

[0038] For example, the aforementioned special effects algorithm switch state is used to indicate whether the special effects algorithm is turned on. The special effects algorithm may include beautification effects, background blur effects, sticker addition effects, character deformation effects, etc., and this application embodiment does not limit this.

[0039] In some embodiments of this application, the temperature-related data may also include environmental parameters of the environment in which the electronic device is located, which may include at least one of the following: ambient temperature, ambient humidity, and ambient wind speed.

[0040] In some embodiments of this application, the electronic device can collect the aforementioned temperature-related data through the data acquisition layer and send the temperature-related data to the prediction unit through the data acquisition layer. In other words, the aforementioned data acquisition layer is responsible for the real-time collection and aggregation of multi-dimensional data.

[0041] In some embodiments of this application, the data acquisition layer described above can be a hardware unit in an electronic device, or a software platform in an electronic device or a virtual module in a software platform.

[0042] In some embodiments of this application, the aforementioned data acquisition layer may include a temperature acquisition module for acquiring the temperature of each processor from a temperature sensor array included in the electronic device. The temperature sensor array includes multiple temperature sensors deployed near critical heat sources in electronic devices such as the SOC, CIS, and power supply, for monitoring the temperatures of these components. Specifically, the temperature sensors deployed near the SOC are deployed near the CPU, GPU, and ISP to monitor their temperatures.

[0043] In some embodiments of this application, the data acquisition layer may include a power consumption monitoring module, which is used to collect load data of high-load modules such as CPU, GPU, ISP, and CSI. The load data includes operating power consumption and operating frequency, or the load data includes operating power consumption.

[0044] In some embodiments of this application, the data acquisition layer may include an environmental parameter module, which is used to acquire environmental parameters such as ambient temperature, ambient humidity, and ambient wind speed of the environment in which the electronic device is located.

[0045] In some embodiments of this application, the data acquisition layer described above may include a task parameter layer, which is used to acquire task parameters of tasks performed by the electronic device.

[0046] In some embodiments of this application, the task performed by the electronic device is a video recording task. The aforementioned task parameter layer can be a camera application layer, which is used to obtain the recording parameters of the current video recording. These recording parameters may include resolution, frame rate, encoding format, and special effects algorithm on / off status, etc.

[0047] In some embodiments of this application, the aforementioned currently collected temperature-related data can be the temperature-related data at the current moment, and the aforementioned historical temperature-related data can be the temperature-related data collected over a historical period of time.

[0048] In some embodiments of this application, step 101 can be implemented by step 1011.

[0049] Step 1011: The electronic device processes the currently collected temperature-related data and the historically collected temperature-related data through the prediction model in the prediction unit to obtain the first temperature change trend data and the first load change trend data of the processor in the electronic device within the first time period in the future.

[0050] In some embodiments of this application, the prediction unit can be a prediction engine, which can also be called an artificial intelligence (AI) prediction engine, and the prediction model can also be called an AI prediction model.

[0051] In some embodiments of this application, the above-described prediction model can be used to predict the processor's heat generation over a future period of time.

[0052] In some embodiments of this application, the prediction model described above can be a lightweight deep learning model, such as a Temporal Convolutional Network (TCN) or a lightweight Long Short-Term Memory (LSTM) network optimized through pruning and quantization. Before being deployed in electronic devices, this prediction model has been trained in the laboratory using a massive dataset covering various environmental conditions, task parameters, temperature data, and load data combinations to accurately learn the nonlinear mapping relationship from the current system state to future thermal behavior. During actual operation, the prediction model in this prediction engine, based on currently collected temperature-related data (such as task parameters, temperature data of each processor, and load data) and historically collected temperature-related data, predicts the first temperature change trend data and the first load change trend data of key heat sources in electronic devices such as CPUs, GPUs, and CIS within a first time period.

[0053] In some embodiments of this application, the value range of the first duration can be (10 seconds, 60 seconds), for example, the first duration can be 10 seconds or 30 seconds.

[0054] In some embodiments of this application, the electronic device can use the prediction unit described above to add up the load change trend data of multiple processors to obtain the total load change trend data of the electronic device.

[0055] In some embodiments of this application, each processor may correspond to a first temperature change trend data and a first load change trend data. Each first temperature change trend data may include first temperature values ​​at multiple times within a future first time period, and each first load change trend data may include first load values ​​at multiple times within a future first time period.

[0056] In some embodiments of this application, load data can be power consumption data, load change trend data can be power consumption change trend data, and load value can be power consumption value.

[0057] In some embodiments of this application, the aforementioned temperature change trend data can be represented in the form of a temperature change curve. Similarly, the aforementioned load change trend data can be represented in the form of a load change curve.

[0058] Thus, by using AI prediction models to predict the future temperature and load changes of electronic devices based on current and historical temperature change data, we can anticipate the future thermal behavior of electronic devices and take preventative measures to avoid overheating, thereby improving the performance of electronic devices.

[0059] Step 102: The electronic device, through the decision unit, determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and sends an execution command to the target object indicated by the target temperature control strategy.

[0060] In some embodiments of this application, the decision-making unit may be a hardware unit in an electronic device, such as a decision engine, or the decision-making unit may be a software platform in an electronic device or a virtual module in a software platform.

[0061] In some embodiments of this application, the above-mentioned target temperature control strategy can be a strategy for controlling the temperature of electronic devices. Executing the target temperature control strategy can ensure that the temperature of the electronic devices does not exceed a safe threshold, thereby preventing the electronic devices from overheating.

[0062] In some embodiments of this application, after the electronic device determines the target temperature control strategy through the decision unit, it can generate an execution instruction corresponding to the target temperature control strategy and send the execution instruction to the target object indicated by the target object identifier.

[0063] In some embodiments of this application, the target object described above can be a target object included in the system's execution layer. For example, the target object can be a device included in a cloud device or electronic device.

[0064] In some embodiments of this application, the above execution instructions can be used to instruct the target object to execute the target temperature control strategy.

[0065] In some embodiments of this application, the electronic device can use a decision unit to simulate the heating situation of the electronic device in the future first time period after adopting different reference temperature control strategies, based on the currently collected temperature-related data, first temperature change trend data and first load change trend data. This allows the electronic device to determine the reference temperature control strategy that prevents the electronic device from overheating as the target temperature control strategy. Then, an execution instruction is sent to the target object to make the target object execute the target temperature control strategy to ensure that the electronic device will not overheat in the future.

[0066] In some embodiments of this application, each first temperature change trend data includes first temperature values ​​at multiple moments within a future first time period; the "determining the target temperature control strategy by the decision unit based on the currently collected temperature-related data, first temperature change trend data and first load change trend data" in step 102 above can be specifically implemented through the following step 1021.

[0067] Step 1021: If, based on the first temperature change trend data, it is determined that any first temperature value of any processor of the electronic device is higher than the first threshold within the first time period in the future, the electronic device, through the decision unit, determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data.

[0068] In some embodiments of this application, after the prediction unit predicts the first temperature change trend data and the first load change trend data, the first temperature change trend data and the first load change trend data are sent to the decision unit. The electronic device determines whether there is a processor whose future temperature value is higher than the first threshold, that is, the future temperature of a processor is about to be too high. If so, the electronic device determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data and the first load change trend data through the decision unit.

[0069] In some embodiments of this application, the aforementioned first threshold can be understood as the maximum temperature value that does not affect the performance of the electronic device or processor. This first threshold can be set based on experience or actual needs; for example, it can be 42 degrees, 45 degrees, or 48 degrees, and this application does not limit this setting.

[0070] In some embodiments of this application, for any processor's corresponding first temperature change trend data, the electronic device can determine whether there is a first temperature value higher than a first threshold among the multiple first temperature values ​​included in the first temperature change trend data. If so, it indicates that the processor will soon experience excessively high temperatures. In this case, the electronic device can determine a target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data through a decision unit.

[0071] In this way, when the electronic device predicts that the temperature of any processor will become too high in the future, it determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, instead of determining the target temperature control strategy for every prediction. This can reduce unnecessary operations, thereby reducing the amount of data processing in the electronic device, reducing the power consumption of the electronic device, and to some extent preventing the electronic device from overheating.

[0072] The step 102 above, "determine the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data by the decision-making unit", can be specifically implemented through the following step 1022.

[0073] Step 1022: The electronic device determines the shell temperature change trend data of the electronic device through the decision unit. If any shell temperature value in the shell temperature change trend data of the electronic device is higher than the first threshold in the first time period, the electronic device determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data and the first load change trend data through the decision unit.

[0074] In some embodiments of this application, the electronic device may employ a prediction model in the decision unit to predict the case temperature change trend data of the electronic device based on the first temperature change trend data of the processor in the electronic device. The case temperature change trend data includes the case temperature values ​​at multiple moments within a future first time period.

[0075] In some embodiments of this application, the target temperature control strategy can also be determined directly through the first temperature change trend data of the processor in the electronic device predicted by the decision unit.

[0076] The aforementioned prediction model can be an AI prediction model, which has the ability to determine the casing temperature of an electronic device based on the temperature of the processor in the electronic device.

[0077] In some embodiments of this application, the aforementioned casing temperature value may refer to the casing temperature of the electronic device, and the casing temperature change trend data may be understood as the casing temperature change trend data of the electronic device within a first time period in the future, used to represent the change trend of the casing temperature of the electronic device.

[0078] In some embodiments of this application, after determining the case temperature change trend data, the electronic device can determine whether the case temperature of the electronic device will be higher than a first threshold in the future first time period. If so, it means that the temperature of the electronic device will be too high in the future. Then, the electronic device can determine the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data and the first load change trend data through the decision unit.

[0079] In this way, when the electronic device's case temperature is predicted to be too high in the future, the decision unit determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, instead of determining the target temperature control strategy for every prediction. This can reduce unnecessary operations, thereby reducing the amount of data processing in the electronic device, lowering the power consumption of the electronic device, and to some extent preventing the electronic device from overheating.

[0080] In some embodiments of this application, combined with Figure 1 ,like Figure 2 As shown, the step 102, step 1021, or step 1022 above, "determine the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data through the decision unit", can be specifically implemented through the following steps 1023 and 1024.

[0081] Step 1023: The electronic device, through the decision unit, predicts at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data.

[0082] In some embodiments of this application, the decision engine described above may also be referred to as an intelligent control decision engine.

[0083] In some embodiments of this application, the temperature change trend data corresponding to one of the at least one reference temperature control strategies is: the temperature change trend data of the electronic device in the second time period in the future when a reference temperature control strategy is adopted.

[0084] It should be noted that the temperature change trend data of the electronic device in the embodiments of this application may refer to the temperature change trend data of the electronic device's casing, that is, the temperature change trend data of the electronic device's casing.

[0085] In some embodiments of this application, at least one reference temperature control strategy is pre-configured in the electronic device. The electronic device can use a decision unit to simulate the future heat generation of the electronic device when it adopts different reference temperature control strategies among the at least one reference temperature control strategy, based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data. That is, it can determine the temperature change trend data of the electronic device in the second time period in the future.

[0086] In some embodiments of this application, the electronic device can use a model predictive control algorithm in the decision unit to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, first temperature change trend data, and first load change trend data.

[0087] In some embodiments of this application, for any reference temperature control strategy, the electronic device can first use a prediction unit to predict the load change trend data of each processor in the electronic device within a future second time period based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and determine the temperature change trend data of each processor based on the load change trend data of each processor, and then predict the temperature change trend data of the electronic device based on the temperature change trend data of each processor, thereby obtaining the temperature change trend data corresponding to the any reference temperature control strategy.

[0088] In some embodiments of this application, the electronic device can also predict the total load change trend data of the electronic device based on the load change trend data of each processor through a decision unit. For example, the electronic device can use the sum of the load change trend data of multiple processors as the total load change trend data of the electronic device.

[0089] In some embodiments of this application, the temperature change trend data corresponding to a reference temperature control strategy may include temperature values ​​at multiple times within a future second time period, that is, the temperature change trend data corresponding to a reference temperature control strategy may include multiple temperature values.

[0090] Step 1024: If the target temperature change trend data meets the temperature control conditions, the electronic device will determine the reference temperature control strategy corresponding to the target temperature change trend data as the target temperature control strategy.

[0091] In some embodiments of this application, the target temperature change trend data can be any one of at least one temperature change trend data.

[0092] In some embodiments of this application, the aforementioned temperature control conditions can be the temperature control conditions corresponding to a reference temperature control strategy that corresponds to the target temperature change trend data. In other words, different reference temperature control strategies may correspond to different temperature control conditions.

[0093] In some embodiments of this application, the aforementioned target temperature change trend data satisfying the temperature control conditions can be understood as follows: when using the reference temperature control strategy corresponding to the target temperature change trend data, the future temperature of the electronic device will not be too high and can be maintained within a safe range. In other words, the aforementioned target temperature control strategy can be understood as a strategy that can continuously maintain the temperature of the electronic device within a safe range.

[0094] In this way, the electronic device, through the decision unit, predicts the temperature change trend data of the electronic device under different reference temperature control strategies. When a certain temperature change trend data meets the temperature control conditions corresponding to the reference temperature control strategy, the reference temperature control conditions corresponding to that temperature change trend data are determined as a strategy that can keep the temperature of the electronic device within a safe range in the future. This allows the temperature control strategy to be used subsequently to control the temperature of the electronic device without affecting the execution of the task, thus preventing the electronic device from overheating in advance.

[0095] In some embodiments of this application, combined with Figure 2 ,like Figure 3 As shown, step 1023 above can be implemented through the following step 10231.

[0096] Step 10231: The electronic device, through the decision unit, predicts at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and based on the priority of at least two reference temperature control strategies.

[0097] In some embodiments of this application, the electronic device can, through a decision unit, predict the temperature change trend data corresponding to the first priority (highest priority) reference temperature control strategy based on the priority of at least two reference temperature control strategies. When the temperature change trend data meets the corresponding temperature control conditions, the reference temperature control strategy with the highest priority is adopted. When the temperature change trend data does not meet the corresponding temperature control conditions, the temperature change trend data corresponding to the second priority reference temperature control strategy is predicted, and so on, until the target temperature control strategy is found.

[0098] In other words, if the electronic device determines that the current reference temperature control strategy cannot suppress the future heat generation of the electronic device, it can then simulate the future heat generation of the electronic device under the next priority reference temperature control strategy; if the current reference temperature control strategy can suppress the future heat generation of the electronic device, the electronic device will determine the current reference temperature control strategy as the target temperature control strategy.

[0099] In this way, the future heat generation of electronic devices is predicted according to the priority of the reference temperature control strategy. When a certain reference temperature control strategy can ensure that the electronic device will not overheat in the future, the temperature change trend data corresponding to the next priority reference temperature control strategy will no longer be predicted. This not only reduces the prediction workload of electronic devices, but also improves the efficiency of determining the target temperature control strategy.

[0100] In some embodiments of this application, the above-mentioned at least two reference temperature control strategies may include an active heat dissipation strategy and an intelligent computing load dynamic migration strategy. The intelligent computing load dynamic migration strategy may include a heat sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy.

[0101] In some embodiments of this application, the above-mentioned at least two reference temperature control strategies may include an active heat dissipation strategy, a thermal sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy.

[0102] In some embodiments of this application, the priority of the above-mentioned at least two reference temperature control strategies, from high to low, is as follows: active heat dissipation strategy, thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

[0103] In some embodiments of this application, the electronic device can use a decision unit to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy, based on currently collected temperature-related data, first temperature change trend data, and first load change trend data, in the order of active heat dissipation strategy, thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

[0104] The priority of the reference temperature control strategy can be adjusted adaptively according to actual needs, and this application does not make specific limitations on it.

[0105] In some embodiments of this application, the electronic device can, through a decision unit, simulate the temperature change trend data corresponding to an active heat dissipation strategy based on currently collected temperature-related data, first temperature change trend data, and first load change trend data. If the temperature change trend data corresponding to the active heat dissipation strategy meets the temperature control conditions corresponding to the active heat dissipation strategy, it indicates that the active heat dissipation strategy can suppress the future heat generation of the electronic device, and the active heat dissipation strategy can be determined as the target temperature control strategy. If the temperature change trend data corresponding to the active heat dissipation strategy does not meet the temperature control conditions corresponding to the active heat dissipation strategy, it indicates that the active heat dissipation strategy cannot suppress the future heat generation of the electronic device, and the electronic device can, through the decision unit, continue to simulate the temperature change trend data corresponding to a thermal sensing task migration strategy. If the temperature change trend data corresponding to the thermal sensing task migration strategy meets the temperature control conditions corresponding to the thermal sensing task migration strategy, it indicates that the thermal sensing task migration strategy can suppress the future heat generation of the electronic device, and the thermal sensing task migration strategy can be determined as the target temperature control strategy. If the temperature change trend data corresponding to the thermal sensing task migration strategy does not meet the temperature control conditions corresponding to the thermal sensing task migration strategy, it indicates that the thermal sensing task migration strategy cannot suppress the future heat generation of the electronic device, and the electronic device can, through the decision unit, continue to simulate the temperature change trend data corresponding to an image sensor load reduction strategy. Similarly, electronic devices can ultimately determine the target temperature control strategy through the decision-making unit.

[0106] In some embodiments of this application, the above-mentioned at least one reference temperature control strategy may include an active heat dissipation strategy, which is a strategy of adjusting the current of the heat dissipation device through the drive circuit in the electronic device.

[0107] In some embodiments of this application, the second temperature change trend data corresponding to the above-mentioned active heat dissipation strategy is: when the electronic device adopts the active heat dissipation strategy, the temperature change trend data of the electronic device in the future second time period under different current levels.

[0108] In some embodiments of this application, the electronic device can use a decision unit to predict, based on currently collected temperature-related data, first temperature change trend data, and first load change trend data, the second temperature change trend data of the electronic device under different current levels within a future second time period when the electronic device adopts an active heat dissipation strategy.

[0109] In some embodiments of this application, the electronic device includes a heat dissipation device, which can be an active heat dissipation device. The aforementioned active heat dissipation strategy achieves pre-cooling or precise temperature control of the processor in the electronic device by controlling the current of the heat dissipation device in the electronic device and precisely adjusting the cooling power of the heat dissipation device.

[0110] The aforementioned heat dissipation device can be a fan, a heat sink, or a thermoelectric cooler. If the heat dissipation device is a thermoelectric cooler, it can specifically be a miniature thermoelectric cooler. This thermoelectric cooler is tightly coupled to the motherboard or critical heat source (processor) of the electronic device through a highly thermally conductive material.

[0111] In some embodiments of this application, the electronic device can use a decision unit to simulate, based on the currently collected temperature-related data, first temperature change trend data, and first load change trend data, the second temperature change trend data of the electronic device when the current of the heat dissipation device is adjusted to different current levels by the drive circuit of the electronic device under the active heat dissipation strategy, and obtain the second temperature change trend data corresponding to different current levels.

[0112] In some embodiments of this application, the aforementioned second temperature change trend data may include second temperature values ​​at multiple moments within a future second time period. The temperature control condition corresponding to the aforementioned active heat dissipation strategy is: at at least one current setting, the second temperature value in the second temperature change trend data is less than a first threshold.

[0113] In some embodiments of this application, if in the second temperature change trend data corresponding to different current levels, there exists at least one current level where some or all of the second temperature values ​​are less than the first threshold, then the active heat dissipation strategy is determined to be the target temperature control strategy.

[0114] For example, assuming different current levels include current level 1, current level 2 and current level 3, if all second temperature values ​​in the second temperature change trend data corresponding to current level 1 and current level 2 are less than the first threshold, then the active heat dissipation strategy can be determined as the target temperature control strategy.

[0115] In some embodiments of this application, the target temperature control strategy is an active heat dissipation strategy, and the target object indicated by the target temperature control strategy is a driving circuit; the "sending an execution instruction to the target object indicated by the target temperature control strategy through the decision unit" in step 102 can be specifically implemented through the following steps 1025 and 1026.

[0116] Step 1025: The electronic device generates a current adjustment command corresponding to the active heat dissipation strategy through the decision unit.

[0117] In some embodiments of this application, the current adjustment command includes a target current level, which can be the smallest current level among at least one current level.

[0118] In some embodiments of this application, the electronic device can use a decision unit to select the smallest current level among at least one current level as the target current level. For example, assuming that at least one current level includes current level 1 and current level 2, and current level 1 is smaller than current level 2, then current level 1 can be determined as the target current level.

[0119] In some embodiments of this application, the electronic device can, through a decision unit, simulate, based on currently collected temperature-related data, first temperature change trend data, and first load change trend data, multiple current levels in ascending order of low to high, the second temperature change trend data corresponding to the at least one current level when the current of the heat dissipation device is adjusted to at least one current level by the drive circuit of the electronic device under an active heat dissipation strategy.

[0120] In some embodiments of this application, the electronic device can, through a decision unit, predict the second temperature change trend data corresponding to the lowest current level based on currently collected temperature-related data, first temperature change trend data, and first load change trend data. If the second temperature value in the second temperature change trend data corresponding to the lowest current level is less than a first threshold, then the active cooling strategy is determined as the target temperature control strategy, and the lowest current level is determined as the target current level. If the second temperature value in the second temperature change trend data corresponding to the lowest current level is greater than the first threshold, then the second temperature change trend data corresponding to a higher current level is predicted. If the second temperature value in the second temperature change trend data corresponding to the higher current level is less than the first threshold, then the active cooling strategy is determined as the target temperature control strategy, and the higher current level is determined as the target current level. This process continues until it is determined that the active cooling strategy cannot control the future temperature of the electronic device within a safe range, or until a target current level is determined.

[0121] Step 1026: The electronic device sends a current adjustment command to the drive circuit through the decision unit.

[0122] In some embodiments of this application, the above-mentioned current adjustment command can be used to instruct the drive circuit to adjust the current of the heat dissipation device in the electronic device based on the target current level.

[0123] In some embodiments of this application, the electronic device sends a current adjustment command to the drive circuit through a decision unit. Then, the drive circuit precisely adjusts the current output to the heat dissipation device to the target current level, thereby controlling the cooling power of the heat dissipation device to ensure that the electronic device will not overheat in the future.

[0124] In some embodiments of this application, the electronic device may include an active cooling execution unit, which may include a heat dissipation device and a drive circuit. The electronic device may send a current adjustment command to the drive circuit through a decision unit. After receiving the current adjustment command, the drive circuit may adjust the current of the heat dissipation device based on a target current level.

[0125] In this way, the electronic device, through the decision-making unit, proactively drives the heat dissipation device (semiconductor cooling chip) to work based on the prediction results, significantly advancing the heat dissipation action, effectively suppressing heat peaks, and preventing the processor in the electronic device from overheating.

[0126] In some embodiments of this application, if the electronic device, through a decision unit, determines that under an active cooling strategy, even if the heat dissipation device continues to operate at maximum safe power, the case temperature of the electronic device will still exceed a first threshold, the electronic device can simulate the future heat dissipation under a more advanced temperature control strategy. This more advanced temperature control strategy no longer relies on traditional parameter degradation strategies that sacrifice image quality, but rather on an intelligent dynamic migration strategy for computing load. The core principle of this strategy is: while maintaining the specifications (resolution, frame rate, image quality) of the final output video, to reduce the real-time computing load of each processor through system-level intelligent scheduling, optimizing from the data source and computing process.

[0127] Thus, a layered collaborative temperature control strategy is constructed. When the active heat dissipation strategy can suppress the temperature rise, the active heat dissipation method is used to cool down first. When the active heat dissipation strategy is still insufficient to suppress the temperature rise, an intelligent computing load dynamic migration strategy is adopted to intelligently and smoothly adjust the computing load instead of directly reducing the recording parameters, so as to ensure that the tasks processed by the electronic device are not interrupted.

[0128] In some embodiments of this application, the at least one reference temperature control strategy mentioned above includes a thermal sensing task migration strategy, which is a strategy for migrating a subtask of any processor to another processor for processing.

[0129] In some embodiments of this application, the above-described thermal sensing task migration strategy controls the temperature of the processor in the electronic device by performing task migration within the SOC.

[0130] In some embodiments of this application, the third temperature change trend data corresponding to the above-mentioned thermal sensing task migration strategy is: when the electronic device adopts the thermal sensing task migration strategy, under different sub-tasks in the migration task, the temperature change trend data of the electronic device in the second time period in the future.

[0131] In some embodiments of this application, the third temperature change trend data corresponding to the above-mentioned thermal sensing task migration strategy is: when the electronic device adopts the thermal sensing task migration strategy, the temperature change trend data of the electronic device in the second time period in the future under different migration strategies.

[0132] In some embodiments of this application, the electronic device can use a decision unit to simulate the temperature change trend data of the electronic device in the second time period under different migration strategies (i.e. different sub-tasks in the migration task) when the electronic device adopts a thermal sensing task migration strategy, and obtain the third temperature change trend data corresponding to at least two migration strategies.

[0133] The aforementioned migration strategy refers to migrating a subtask from one processor to another. In some embodiments of this application, the aforementioned third temperature change trend data includes third temperature values ​​at multiple moments within a future second time period. The temperature control condition corresponding to the aforementioned thermal sensing task migration strategy is: when migrating any subtask, the third temperature value in the third temperature change trend data is less than a first threshold.

[0134] In some embodiments of this application, if in the third temperature change trend data corresponding to at least two migration strategies, there exists at least one migration strategy (i.e., migrating any sub-task) whose third temperature change trend data contains some or all of the third temperature values ​​that are less than the first threshold, then the thermal sensing task migration strategy is determined to be the target temperature control strategy.

[0135] In some embodiments of this application, the temperature control condition corresponding to the above-mentioned thermal sensing task migration strategy is: there exists a third temperature value in the third temperature change trend data corresponding to at least one migration strategy that is less than a first threshold.

[0136] For example, suppose at least two migration strategies include migration strategy 1, migration strategy 2 and migration strategy 3. Migration strategy 1 is to migrate subtask 1 in processor A to processor B. Migration strategy 2 is to migrate subtasks 1 and 2 in processor A to processor B. Migration strategy 3 is to migrate subtask 2 in processor A to processor B. If all third temperature values ​​in the third temperature change trend data corresponding to migration strategy 1 and migration strategy 2 are less than the first threshold, then the thermal sensing task migration strategy can be determined as the target temperature control strategy.

[0137] In some embodiments of this application, the target temperature control strategy is a thermal sensing task migration strategy, and the target object indicated by the target temperature control strategy is the thermal sensing task scheduler in the electronic device; the "sending execution instructions to the target object indicated by the target temperature control strategy through the decision unit" in step 102 can be specifically implemented through the following steps 1027 and 1028.

[0138] Step 1027: The electronic device generates a task migration instruction corresponding to the thermal sensing task migration strategy through the decision unit.

[0139] In some embodiments of this application, the above-mentioned task migration instruction includes a first processor identifier, a second processor identifier, and a task identifier.

[0140] In some embodiments of this application, the electronic device can, through a decision unit, predict the third temperature change trend data corresponding to at least two migration strategies, and simultaneously predict the total load change trend data corresponding to at least two migration strategies, that is, the total load change trend data of the electronic device within a future second time period when migrating different sub-tasks. Then, the electronic device can determine the migration strategy in which each load value in the total load change trend data corresponding to the above-mentioned at least one migration strategy is less than the third threshold as the target migration strategy, and obtain the first processor identifier, the second processor identifier, and the task identifier corresponding to the target migration strategy.

[0141] In some embodiments of this application, the electronic device can use a decision unit to simulate, based on currently collected temperature-related data, first temperature change trend data, and first load change trend data, the third temperature change trend data corresponding to at least two migration strategies in descending order of priority of at least two migration strategies, when migrating a subtask of one processor to another processor under the thermal sensing task migration strategy.

[0142] In some embodiments of this application, the electronic device can, through a decision unit, predict the third temperature change trend data corresponding to a first-priority migration strategy based on currently collected temperature-related data, first temperature change trend data, and first load change trend data. If the third temperature value in the third temperature change trend data corresponding to the first-priority migration strategy is less than a first threshold, then the thermal sensing task migration strategy is determined as the target temperature control strategy, and the first-priority migration strategy is determined as the target migration strategy. If the third temperature value in the third temperature change trend data corresponding to the first-priority migration strategy is greater than the first threshold, then the third temperature change trend data corresponding to a second-priority migration strategy is predicted. If the third temperature value in the third temperature change trend data corresponding to the second-priority migration strategy is less than the first threshold, then the thermal sensing task migration strategy is determined as the target temperature control strategy, and the second-priority migration strategy is determined as the target migration strategy. This process continues until it is determined that the thermal sensing task migration strategy cannot control the future temperature of the electronic device within a safe range, or until a target migration strategy is determined.

[0143] In some embodiments of this application, the first temperature change trend data corresponding to each processor of the electronic device may include first temperature values ​​at multiple moments within a future first time period.

[0144] In some embodiments of this application, the processor indicated by the first processor identifier is a processor in the electronic device whose corresponding first temperature change trend data has at least one first temperature value greater than a first threshold. In other words, the processor indicated by the first processor identifier is a processor in the electronic device that is likely to overheat in the future.

[0145] In some embodiments of this application, the processor indicated by the second processor identifier is a processor in the electronic device whose corresponding first temperature value in the first temperature change trend data is less than a first threshold. In other words, the processor indicated by the second processor identifier can be a processor in the electronic device whose future temperature is always less than the first threshold.

[0146] In some embodiments of this application, the processor indicated by the second processor identifier can be the processor in the electronic device whose first temperature value in the corresponding first temperature change trend data is less than a first threshold, is furthest from the processor indicated by the first processor identifier, and has the lowest highest first temperature value in the first temperature change trend data. In other words, the processor indicated by the second processor identifier can be the processor in the electronic device whose future temperature is always less than the first threshold, is furthest from the processor indicated by the first processor identifier, and has a lower future temperature.

[0147] In some embodiments of this application, the task indicated by the above-mentioned task identifier is a task whose computational load, as indicated by the first processor identifier, is greater than a second threshold. The second threshold can be set based on experience or actual needs, and this application does not limit its implementation.

[0148] Step 1028: The electronic device sends a task migration instruction to the thermal sensing task scheduler through the decision unit.

[0149] In some embodiments of this application, the aforementioned heat-sensing task scheduler is a system-level driver with the ability to migrate tasks across processors in real time.

[0150] In some embodiments of this application, the above-mentioned task migration instruction is used to instruct the thermal sensing task scheduler to migrate the subtask indicated by the task identifier from the processor indicated by the first processor identifier to the processor indicated by the second processor identifier for processing.

[0151] For example, taking video recording as an example, when the electronic device predicts that the CPU will overheat through the prediction unit, the electronic device simulates the future heating of the CPU under different reference temperature control strategies through the decision unit. When it is determined that the CPU will not overheat in the future under the heat-sensing task migration strategy, the electronic device can send a task migration instruction to the heat-sensing task scheduler. After receiving the task migration instruction, the heat-sensing task scheduler dynamically migrates the high-load tasks (tasks indicated by task identifiers) waiting for the CPU (the processor indicated by the first processor identifier) ​​in the video processing pipeline to a coprocessor (the processor indicated by the second processor identifier) ​​that is physically far away from the CPU and has a lower temperature for execution.

[0152] For example, the aforementioned high-load tasks could be beautification tasks or focus tracking tasks. The aforementioned coprocessor could be a Neural Network Processing Unit (NPU) or a dedicated Digital Signal Processor (DSP).

[0153] In this way, electronic devices can migrate high-load tasks at the chip level through thermal sensing task strategies, thereby realizing the spatial migration of high-load computing heat sources at the chip level. This fundamentally avoids the situation where a certain processor in the electronic device is too hot and prevents the formation of local heat sources.

[0154] In some embodiments of this application, the electronic device simulates the future heat generation of the electronic device under the thermal sensing task migration strategy through a decision unit. If it is determined that the future heat generation of the electronic device cannot be suppressed under the thermal sensing task migration strategy, the electronic device can simulate the future heat generation of the electronic device under the image sensor load reduction strategy. If it is determined that the future heat generation of the electronic device can be well suppressed under the image sensor load reduction strategy, then the image sensor load reduction strategy is determined as the target temperature control strategy.

[0155] In some embodiments of this application, the task performed by the above-mentioned electronic device is video recording.

[0156] In some embodiments of this application, the at least one reference temperature control strategy described above includes an image sensor load reduction strategy.

[0157] In some embodiments of this application, the above-described image sensor load reduction strategy reduces the load on the processor in the electronic device by reducing the amount of data output by the image sensor, thereby reducing power consumption and achieving temperature control of the electronic device.

[0158] In some embodiments of this application, the fourth temperature change trend data corresponding to the above-mentioned image sensor load reduction strategy is: the temperature change trend data of the electronic device within a second time period in the future when the electronic device adopts the image sensor load reduction strategy.

[0159] In some embodiments of this application, the electronic device can use a decision unit to predict, based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, the second temperature change trend data of the electronic device in the future second time period when the electronic device uses the image sensor load reduction strategy to collect images.

[0160] In some embodiments of this application, the aforementioned fourth temperature change trend data may include fourth temperature values ​​at multiple times within a future second time period. The temperature control condition corresponding to the aforementioned image sensor load reduction strategy is: the fourth temperature value in the fourth temperature change trend data is less than a first threshold.

[0161] For example, the temperature control condition corresponding to the above image sensor load reduction strategy is: some or all of the fourth temperature values ​​in the fourth temperature change trend data are less than the first threshold.

[0162] In some embodiments of this application, the target temperature control strategy is an image sensor load reduction strategy, and the target object indicated by the target temperature control strategy is the image sensor of the electronic device; the "sending an execution instruction to the target object indicated by the target temperature control strategy through the decision unit" in step 102 can be specifically implemented through the following steps 1029 and 1030.

[0163] Step 1029: The electronic device generates image partition acquisition instructions corresponding to the image sensor load reduction strategy through the decision unit.

[0164] In some embodiments of this application, the above-mentioned image partitioning acquisition instruction includes key region identifiers and redundant region identifiers in the preview image stream.

[0165] In some embodiments of this application, the area indicated by the aforementioned key area marker can be a foreground area or a subject area in the preview image. The area indicated by the aforementioned redundant area marker can be a background area in the preview image.

[0166] In some embodiments of this application, the image partitioning acquisition instruction may further include a key region acquisition method and a redundant region acquisition method. The key region acquisition method is full-resolution acquisition, and the redundant region acquisition method information includes at least one of partition pixel merging acquisition and inter-frame reading.

[0167] Step 1030: The electronic device sends an image partition acquisition command to the image sensor through the decision unit.

[0168] In some embodiments of this application, the above-mentioned image partitioning acquisition instruction is used to instruct the image sensor to perform partitioned pixel merging acquisition of the key area indicated by the key area identifier in the preview image stream during video recording, and to perform at least one of the following: partitioned pixel merging acquisition of the redundant area indicated by the redundant area identifier in the preview image stream, and frame-by-frame reading of the pixels of the redundant area in the preview image stream.

[0169] In some embodiments of this application, the aforementioned partitioned pixel merging acquisition may refer to accumulating or averaging the photoelectric signals of multiple adjacent pixels (such as 2×2 or 4×4) in the pixel array of the image sensor, and then outputting a merged signal value, rather than outputting pixel by pixel, which can reduce the number of output pixels. The aforementioned inter-frame reading may refer to reading the redundant area only once every N frames, or reducing the readout clock frequency when reading pixels in the redundant area, resulting in fewer rows / columns of pixels read in the same amount of time.

[0170] In some embodiments of this application, the aforementioned image partitioning acquisition instruction can be used to instruct the image sensor to perform full-resolution acquisition of the area indicated by the key area marker in the preview image stream during video recording, and to perform partitioned pixel merging acquisition of the redundant area indicated by the redundant area marker in the preview image stream. Alternatively, the aforementioned image partitioning acquisition instruction can be used to instruct the image sensor to perform full-resolution acquisition of the area indicated by the key area marker in the preview image stream during video recording, and to perform frame-by-frame reading of the redundant area indicated by the redundant area marker in the preview image stream. Alternatively, the aforementioned image partitioning acquisition instruction can be used to instruct the image sensor to perform full-resolution acquisition of the area indicated by the key area marker in the preview image stream during video recording, and to perform partitioned pixel merging acquisition of the redundant area indicated by the redundant area marker in the preview image stream and to read the pixels of the redundant area frame-by-frame.

[0171] In some embodiments of this application, the electronic device can identify key and redundant regions in the preview stream through the NPU and send the identification results to the decision engine.

[0172] For example, taking video recording as an example, when the electronic device predicts that one or more processors are about to overheat through the prediction unit, the electronic device simulates the heat generation under different reference temperature control strategies through the decision unit. If it is determined that the electronic device will not overheat under the image sensor load reduction strategy, the electronic device can analyze the preview image stream in real time through the NPU, identify key and redundant areas in the preview image stream, and then send image partitioning acquisition commands to the image sensor, dynamically configuring the image sensor's readout mode. Key areas are acquired at full resolution, while redundant areas are acquired using methods such as partitioned pixel merging and reduced readout frequency. Furthermore, the electronic device can also compensate for the redundant areas using algorithms to maintain the final image quality.

[0173] In some embodiments of this application, the aforementioned image partitioning acquisition command may further include an interface identifier. The electronic device can send the image partitioning acquisition command to the image sensor control interface indicated by the interface identifier via a decision unit. Then, the image sensor control interface sends the image partitioning acquisition command to the image sensor via a transmission interface to dynamically configure the partitioning acquisition parameters when the image sensor acquires images. The transmission interface may be a hardware interface such as a Mobile Industry Processor Interface (MIPI).

[0174] In this way, electronic devices reduce the amount of data in the images acquired by the image sensor through image sensor load reduction strategies, that is, reduce the amount of output data from the physical source. Ultimately, the total amount of data transmitted from the image sensor to the image signal processor will also be greatly reduced, enabling the image signal processor to operate with low power consumption, reducing the power consumption of the image signal processor, and avoiding excessive heat generation of the image signal processor.

[0175] In some embodiments of this application, the electronic device simulates the future heat generation under the image sensor load reduction strategy through a decision unit. If it is determined that the future heat generation of the electronic device cannot be suppressed under the image sensor load reduction strategy, the electronic device can simulate the future heat generation under the cloud processing strategy. If it is determined that the future heat generation of the electronic device can be well suppressed under the cloud processing strategy, then the cloud processing strategy is determined as the target temperature control strategy.

[0176] In some embodiments of this application, the at least one reference temperature control strategy mentioned above includes a cloud processing strategy, which migrates task data of tasks performed by electronic devices to cloud devices for processing.

[0177] In some embodiments of this application, the above-mentioned cloud processing strategy reduces the power consumption of electronic devices by transmitting the tasks performed by electronic devices to cloud devices for execution, thereby achieving temperature control of electronic devices.

[0178] In some embodiments of this application, the fifth temperature change trend data corresponding to the above-mentioned cloud processing strategy is: the temperature change trend data of the electronic device within a future second time period when the electronic device adopts the cloud processing strategy.

[0179] In some embodiments of this application, the aforementioned fifth temperature change trend data includes the fifth temperature value at multiple moments within a future second time period, and the temperature control condition corresponding to the aforementioned cloud processing strategy is: the fifth temperature value in the fifth temperature change trend data is less than the first threshold.

[0180] In some embodiments of this application, the target temperature control strategy is a cloud processing strategy, and the target object indicated by the target temperature control strategy is a cloud device; the "sending an execution instruction to the target object indicated by the target temperature control strategy through the decision unit" in step 102 can be specifically implemented through the following steps 1031 and 1032.

[0181] Step 1031: The electronic device generates cloud migration instructions corresponding to the cloud processing strategy through the decision unit.

[0182] In some embodiments of this application, the cloud migration instructions described above include task data of the tasks performed by the electronic device.

[0183] In some embodiments of this application, the task currently being performed by the electronic device is a video recording task, and the task data may be the recorded raw video stream (RAW video stream) or encoded data obtained by encoding the raw video stream.

[0184] Step 1032: The electronic device sends a cloud migration command to the cloud device through the decision unit.

[0185] In some embodiments of this application, the cloud migration instructions described above can be used to instruct cloud devices to process task data and feed back the processed data to electronic devices.

[0186] For example, taking video recording as an example, when the aforementioned temperature control strategies are insufficient to control the processor temperature in the electronic device in the future, the electronic device can utilize high-speed mobile networks to initiate cloud migration. Specifically, the electronic device, through a decision unit, controls the recording of video to obtain a raw video stream, which is then uploaded to a cloud device in real time. Alternatively, the raw video stream can be encoded, and the encoded data can be uploaded to the cloud device in real time. The cloud device then processes the encoded data to obtain a finished video stream, which is then fed back to the electronic device, thereby overcoming the limitations of local hardware thermal limitations in recording capabilities.

[0187] In this way, by transferring data that was originally processed by electronic devices to cloud devices, the amount of data processing by electronic devices is reduced, the power consumption of electronic devices is lowered, and overheating of electronic devices can be avoided.

[0188] In some embodiments of this application, the data processing layer can collect temperature-related data in real time, and optimize and adaptively adjust the AI ​​prediction model and reference temperature control strategy online through the real-time collected temperature-related data to achieve the best balance between heat dissipation performance and overall power consumption.

[0189] In some embodiments of this application, the electronic device can use a decision unit to simulate the future heat generation of the electronic device under the active heat dissipation strategy, the thermal sensing task migration strategy, the image sensor load reduction strategy, and the cloud processing strategy (i.e., the temperature change trend data of the electronic device in the second future time period mentioned above), and then determine the target temperature control strategy from these four reference temperature control strategies.

[0190] In some embodiments of this application, the electronic device can first predict the temperature change trend data and total load trend data corresponding to each reference temperature control strategy, then determine at least one temperature control reference strategy whose temperature change trend data satisfies the corresponding temperature control conditions, and then determine the temperature control strategy with the smallest total load change trend data among the at least one temperature control reference strategy as the target temperature control strategy.

[0191] The phrase "the minimum total load change trend data" can be understood as the phrase "the minimum maximum load value among the total load change trend data".

[0192] In some embodiments of this application, the electronic device can first simulate the future heat generation of the electronic device under an active heat dissipation strategy through a decision unit. If the active heat dissipation strategy cannot suppress the future temperature of the electronic device, the decision unit can then simulate the future heat generation of the electronic device under a thermal sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy. Finally, the target temperature control strategy is determined from these three reference temperature control strategies.

[0193] In some embodiments of this application, the electronic device can use a decision unit to sequentially simulate the future heating situation of the electronic device under each reference temperature strategy, in the order of thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

[0194] In this way, the electronic device simulates the heat generation of the electronic device when different reference temperature control strategies are adopted through the decision unit, and selects the reference temperature control strategy that keeps the temperature of the electronic device within a safe range and has low total power consumption as the target temperature control strategy, thereby ensuring that the electronic device will not overheat or generate too much power consumption in the future.

[0195] Figure 4 This is a schematic diagram of the temperature control system provided in the embodiments of this application. The temperature control system can be a system in an electronic device, which is a system combining hardware and software. The temperature control system can run the temperature control method provided in the embodiments of this application to control the temperature of the electronic device.

[0196] like Figure 4 As shown, in some embodiments of this application, the temperature control system described above may include a data acquisition layer 41, a prediction unit 42, a decision-making unit 43, and an execution layer 44.

[0197] In some embodiments of this application, the data acquisition layer 41 is used to acquire temperature-related data. Specifically, the data acquisition layer 41 can acquire recording parameters, including resolution, frame rate, encoding format, and special effects algorithm on / off status, from the camera application layer 411. The data acquisition layer 41 can acquire the temperature of the CPU, GPU, ISP, CSI, and battery from the temperature sensor array 412. The data acquisition layer 41 can acquire environmental parameters, such as ambient temperature, ambient humidity, and ambient wind speed, from the environmental parameter module 413. The data acquisition layer 41 can acquire the power consumption of processors such as the CPU, GPU, ISP, and CSI from the power consumption monitoring module 414.

[0198] In some embodiments of this application, the prediction unit 42 can be an AI prediction engine. The decision unit can be an intelligent control decision engine.

[0199] In some embodiments of this application, the data acquisition layer 41 can send the acquired temperature-related data to the AI ​​prediction engine 42. The AI ​​prediction engine 42 uses a lightweight deep learning model LSTM or TCN to predict the temperature change trend data (i.e., the aforementioned first temperature change trend data) and power consumption change trend data (i.e., the aforementioned second load change trend data) of processors such as CPU, GPU, ISP, and CSI in electronic devices based on the temperature-related data. The prediction results are then sent to the intelligent control decision engine 43. The intelligent control decision engine 43 uses a model predictive control algorithm to predict the future heat generation of the CPU, GPU, ISP, and CSI under different reference temperature control strategies, thereby determining the target temperature control strategy. If the target temperature control strategy is an active heat dissipation strategy, the intelligent control decision engine can send an execution command to the active heat dissipation device 441 of the execution layer 44, allowing the active heat dissipation device 441 to actively dissipate heat. If the target temperature control strategy is an intelligent computing load dynamic migration strategy, the intelligent control decision engine can send an execution command to the computing load dynamic migration unit 442 of the execution layer 44, allowing the computing load dynamic migration unit 442 to execute the intelligent computing load dynamic migration strategy.

[0200] In some embodiments of this application, the aforementioned computing load dynamic migration unit 442 can also be referred to as a computing load scheduling and execution unit. This computing load scheduling and execution unit is a hardware and software co-operation system used to execute intelligent computing load dynamic migration strategies. The computing load scheduling and execution unit may include a thermal sensing task scheduler, an image sensor control interface, and a cloud-based collaborative client unit.

[0201] The thermal sensing task scheduler is used to execute thermal sensing task migration strategies.

[0202] The image sensor control interface is used to send image partition acquisition commands to the image sensor through hardware interfaces such as MIPI to dynamically configure the partition readout parameters of the image sensor.

[0203] The cloud-based collaborative client unit is used to manage the recording of local low-complexity video streams, data transmission with the cloud, and synchronization of finished video streams.

[0204] In some embodiments of this application, the temperature control system described above is a closed-loop feedback system. The load dynamic migration unit 442 can feed back the power consumption of the processor after executing the temperature control strategy to the power consumption monitoring module 414, and the active heat dissipation device 441 can feed back the temperature of the processor after active heat dissipation to the temperature sensor array. In this way, by continuously collecting actual system state data (temperature data and load data), the AI ​​prediction model and temperature control strategy can be optimized and adaptively adjusted online, thereby achieving the best balance between heat dissipation efficiency and overall power consumption.

[0205] The temperature control method provided in this application significantly delays overheating through proactive and predictive heat dissipation intervention, allowing electronic devices to maintain high-specification recording for several times longer, breaking through recording time limitations. Furthermore, by using AI prediction, the heat dissipation system can allocate cooling power "on demand," combined with dynamic optimization of computing load, avoiding energy waste and achieving an optimal balance between heat dissipation and device battery life, making it more intelligent and efficient. Moreover, with effective thermal management, the SOC and camera module can operate at high performance for longer periods, fully utilizing the hardware potential of the electronic device, processor, or chip. In addition, this solution avoids sudden interruptions in the recording process; the gradual and intelligent load adjustment strategy makes the user's creative process more predictable and smooth, improving the user experience.

[0206] It should be noted that the specific implementation process of the temperature control system executing the temperature control method can be found in the relevant description of the above embodiments. To avoid repetition, this embodiment will not repeat it here.

[0207] It should be noted that each of the above method embodiments, or various possible implementations of each method embodiment, can be executed individually or in combination of any two or more. The specific implementation can be determined according to actual usage requirements, and this application embodiment does not impose any restrictions on this.

[0208] The temperature control method provided in this application can be executed by a temperature control device. This application uses an example of a temperature control device executing the temperature control method to illustrate the temperature control device provided in this application.

[0209] Figure 5 This is a schematic diagram of the temperature control device provided in the embodiment of this application. The temperature control device includes a prediction unit 501 and a decision unit 502.

[0210] The prediction unit 501 is used to predict the first temperature change trend data and the first load change trend data of the processor in the electronic device within a first time period based on the currently collected temperature-related data and the historically collected temperature-related data.

[0211] The decision unit 502 is used to determine a target temperature control strategy based on currently collected temperature-related data, first temperature change trend data, and first load change trend data, and to send an execution instruction to the target object indicated by the target temperature control strategy. The temperature-related data includes task parameters of the task being performed by the electronic device, as well as the processor's temperature and load data; the execution instruction is used to instruct the target object to execute the target temperature control strategy.

[0212] In some embodiments of this application, the decision unit 502 is specifically configured to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, first temperature change trend data, and first load change trend data; and, if the target temperature change trend data meets the temperature control conditions, determine the reference temperature control strategy corresponding to the target temperature change trend data as the target temperature control strategy.

[0213] Among them, the temperature change trend data corresponding to a reference temperature control strategy is the temperature change trend data of the electronic device in the second time period in the future when a reference temperature control strategy is adopted; the temperature control condition is the temperature control condition corresponding to the reference temperature control strategy corresponding to the target temperature change trend data; the target temperature change trend data is any one of the temperature change trend data in at least one temperature change trend data.

[0214] In some embodiments of this application, the decision unit 502 is specifically used to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, first temperature change trend data, and first load change trend data, and based on the priority of at least two reference temperature control strategies.

[0215] In some embodiments of this application, the above-mentioned at least two reference temperature control strategies include an active heat dissipation strategy, a thermal sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy; wherein, the priority of the at least two reference temperature control strategies from high to low is: active heat dissipation strategy, thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

[0216] In some embodiments of this application, the aforementioned at least one reference temperature control strategy includes an active heat dissipation strategy, which is a strategy of adjusting the current of the heat dissipation device through the drive circuit in the electronic device; the second temperature change trend data corresponding to the active heat dissipation strategy is the temperature change trend data of the electronic device in the future second time period under different current levels when the electronic device adopts the active heat dissipation strategy; the second temperature change trend data includes the second temperature values ​​at multiple moments in the future second time period; the temperature control condition corresponding to the active heat dissipation strategy is: under at least one current level, the second temperature value in the second temperature change trend data is less than a first threshold.

[0217] In some embodiments of this application, the target temperature control strategy is an active heat dissipation strategy, and the target object indicated by the target temperature control strategy is the drive circuit; the decision unit 502 is specifically used to generate a current adjustment command corresponding to the active heat dissipation strategy and to send the current adjustment command to the drive circuit.

[0218] The current adjustment command includes a target current level, which is the smallest current level among at least one current level. The current adjustment command is used to instruct the drive circuit to adjust the current of the heat dissipation device in the electronic device based on the target current level.

[0219] In some embodiments of this application, the at least one reference temperature control strategy mentioned above includes a thermal sensing task migration strategy, which is a strategy to migrate a subtask of any processor to another processor for processing; the third temperature change trend data corresponding to the thermal sensing task migration strategy is the temperature change trend data of the electronic device in the future second time period when the electronic device adopts the thermal sensing task migration strategy and migrates different subtasks in the task; the third temperature change trend data includes the third temperature value at multiple moments in the future second time period; the temperature control condition corresponding to the thermal sensing task migration strategy is: when migrating any subtask, the third temperature value in the third temperature change trend data is less than a first threshold.

[0220] In some embodiments of this application, the target temperature control strategy is a thermal sensing task migration strategy, and the target object indicated by the target temperature control strategy is the thermal sensing task scheduler in the electronic device; the decision unit 502 is specifically used to generate a task migration instruction corresponding to the thermal sensing task migration strategy; and to send the task migration instruction to the thermal sensing task scheduler.

[0221] The task migration instruction includes a first processor identifier, a second processor identifier, and a task identifier. The task migration instruction is used to instruct the thermal sensing task scheduler to migrate the subtask indicated by the task identifier from the processor indicated by the first processor identifier to the processor indicated by the second processor identifier for processing.

[0222] In some embodiments of this application, the electronic device performs a video recording task; at least one reference temperature control strategy includes an image sensor load reduction strategy; the fourth temperature change trend data corresponding to the image sensor load reduction strategy is the temperature change trend data of the electronic device within a future second time period when the electronic device adopts the image sensor load reduction strategy; the fourth temperature change trend data includes the fourth temperature values ​​at multiple moments within the future second time period; the temperature control condition corresponding to the image sensor load reduction strategy is: the fourth temperature value in the fourth temperature change trend data is less than a first threshold.

[0223] In some embodiments of this application, the target temperature control strategy is an image sensor load reduction strategy, and the target object indicated by the target temperature control strategy is the image sensor of the electronic device; the decision unit 502 is specifically used to generate an image partition acquisition instruction corresponding to the image sensor load reduction strategy; and to send the image partition acquisition instruction to the image sensor.

[0224] The image partitioning acquisition instruction includes key area identifiers and redundant area identifiers in the preview image stream. The image partitioning acquisition instruction is used to instruct the image sensor to perform partitioned pixel merging acquisition of the key area indicated by the key area identifier in the preview image stream during video recording, and to perform at least one of the following: partitioned pixel merging acquisition of the redundant area indicated by the redundant area identifier in the preview image stream, and frame-by-frame reading of the pixels of the redundant area in the preview image stream.

[0225] In some embodiments of this application, the above-mentioned at least one reference temperature control strategy includes a cloud processing strategy, which migrates the task data of the task executed by the electronic device to the cloud device for processing; the fifth temperature change trend data corresponding to the cloud processing strategy is the temperature change trend data of the electronic device in the future second time period when the electronic device adopts the cloud processing strategy; the fifth temperature change trend data includes the fifth temperature value at multiple moments in the future second time period; the temperature control condition corresponding to the cloud processing strategy is: the fifth temperature value in the fifth temperature change trend data is less than the first threshold.

[0226] In some embodiments of this application, the target temperature control strategy is a cloud processing strategy, and the target object indicated by the target temperature control strategy is a cloud device; the decision unit 502 is specifically used to generate a cloud migration instruction corresponding to the cloud processing strategy; and to send the cloud migration instruction to the cloud device.

[0227] The cloud migration instruction includes task data for the tasks performed by the electronic device; the cloud migration instruction is used to instruct the cloud device to process the task data and feed back the processed data to the electronic device.

[0228] The temperature control device provided in this application, through a prediction unit, predicts the future power consumption and temperature changes of electronic devices under specific task parameters based on currently collected temperature-related data and historically collected temperature-related data. Based on the prediction results, it proactively employs temperature control strategies to control the temperature, achieving a shift from "passive response" to "active prediction." Compared to cooling down the electronic device only after it has overheated, this solution can proactively control the temperature of the electronic device by implementing temperature control strategies when overheating is predicted, reducing the occurrence of overheating. It also eliminates the need for temperature control through frequency reduction, lowering recording specifications, or directly interrupting the recording process, thus controlling the temperature of the electronic device without affecting task execution.

[0229] The temperature control device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device, augmented reality / virtual reality device, robot, wearable device, super mobile personal computer, netbook, or personal digital assistant, etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the specific implementation.

[0230] The temperature control device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0231] The temperature control device provided in this application can realize the various processes implemented in the various embodiments of the above-described temperature control method. To avoid repetition, it will not be described again here.

[0232] Optionally, such as Figure 6 As shown, this application embodiment also provides an electronic device 900, including a processor 901 and a memory 902. The memory 902 stores a program or instructions that can run on the processor 901. When the program or instructions are executed by the processor 901, they implement the various steps of the above-described temperature control method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0233] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0234] Figure 7 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0235] The electronic device 1000 includes, but is not limited to, components such as: radio frequency unit 1001, network module 1002, audio output unit 1003, input unit 1004, sensor 1005, display unit 1006, user input unit 1007, interface unit 1008, memory 1009, and processor 1010.

[0236] Those skilled in the art will understand that the electronic device 1000 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1010 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 7 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0237] The processor 1010 is used to predict, based on the currently collected temperature-related data and the historically collected temperature-related data, the first temperature change trend data and the first load change trend data of the processor in the electronic device within a future first time period; and to determine the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data and the first load change trend data, and to send an execution instruction to the target object indicated by the target temperature control strategy.

[0238] Temperature-related data includes task parameters of the tasks performed by the electronic device, as well as temperature and load data of the processor; execution instructions are used to instruct the target object to execute the target temperature control strategy.

[0239] In some embodiments of this application, the processor 1010 is specifically configured to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy based on currently collected temperature-related data, first temperature change trend data, and first load change trend data; and, if the target temperature change trend data meets the temperature control conditions, determine the reference temperature control strategy corresponding to the target temperature change trend data as the target temperature control strategy.

[0240] Among them, the temperature change trend data corresponding to a reference temperature control strategy is the temperature change trend data of the electronic device in the second time period in the future when a reference temperature control strategy is adopted; the temperature control condition is the temperature control condition corresponding to the reference temperature control strategy corresponding to the target temperature change trend data; the target temperature change trend data is any one of the temperature change trend data in at least one temperature change trend data.

[0241] In some embodiments of this application, the processor 1010 is specifically used to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy based on the currently collected temperature-related data, first temperature change trend data, and first load change trend data, and based on the priority of at least two reference temperature control strategies.

[0242] In some embodiments of this application, the above-mentioned at least two reference temperature control strategies include an active heat dissipation strategy, a thermal sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy; wherein, the priority of the at least two reference temperature control strategies from high to low is: active heat dissipation strategy, thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

[0243] In some embodiments of this application, the aforementioned at least one reference temperature control strategy includes an active heat dissipation strategy, which is a strategy of adjusting the current of the heat dissipation device through the drive circuit in the electronic device; the second temperature change trend data corresponding to the active heat dissipation strategy is the temperature change trend data of the electronic device in the future second time period under different current levels when the electronic device adopts the active heat dissipation strategy; the second temperature change trend data includes the second temperature values ​​at multiple moments in the future second time period; the temperature control condition corresponding to the active heat dissipation strategy is: under at least one current level, the second temperature value in the second temperature change trend data is less than a first threshold.

[0244] In some embodiments of this application, the target temperature control strategy is an active heat dissipation strategy, and the target object indicated by the target temperature control strategy is the driving circuit; the processor 1010 is specifically used to generate a current adjustment instruction corresponding to the active heat dissipation strategy through the decision unit; and to send the current adjustment instruction to the driving circuit.

[0245] The current adjustment command includes a target current level, which is the smallest current level among at least one current level. The current adjustment command is used to instruct the drive circuit to adjust the current of the heat dissipation device in the electronic device based on the target current level.

[0246] In some embodiments of this application, the at least one reference temperature control strategy mentioned above includes a thermal sensing task migration strategy, which is a strategy to migrate a subtask of any processor to another processor for processing; the third temperature change trend data corresponding to the thermal sensing task migration strategy is the temperature change trend data of the electronic device in the future second time period when the electronic device adopts the thermal sensing task migration strategy and migrates different subtasks in the task; the third temperature change trend data includes the third temperature value at multiple moments in the future second time period; the temperature control condition corresponding to the thermal sensing task migration strategy is: when migrating any subtask, the third temperature value in the third temperature change trend data is less than a first threshold.

[0247] In some embodiments of this application, the target temperature control strategy is a thermal sensing task migration strategy, and the target object indicated by the target temperature control strategy is the thermal sensing task scheduler in the electronic device; the decision processor 1010 is specifically used to generate a task migration instruction corresponding to the thermal sensing task migration strategy; and to send the task migration instruction to the thermal sensing task scheduler.

[0248] The task migration instruction includes a first processor identifier, a second processor identifier, and a task identifier. The task migration instruction is used to instruct the thermal sensing task scheduler to migrate the subtask indicated by the task identifier from the processor indicated by the first processor identifier to the processor indicated by the second processor identifier for processing.

[0249] In some embodiments of this application, the electronic device performs a video recording task; at least one reference temperature control strategy includes an image sensor load reduction strategy; the fourth temperature change trend data corresponding to the image sensor load reduction strategy is the temperature change trend data of the electronic device within a future second time period when the electronic device adopts the image sensor load reduction strategy; the fourth temperature change trend data includes the fourth temperature values ​​at multiple moments within the future second time period; the temperature control condition corresponding to the image sensor load reduction strategy is: the fourth temperature value in the fourth temperature change trend data is less than a first threshold.

[0250] In some embodiments of this application, the target temperature control strategy is an image sensor load reduction strategy, and the target object indicated by the target temperature control strategy is the image sensor of the electronic device; the processor 1010 is specifically used to generate an image partition acquisition instruction corresponding to the image sensor load reduction strategy; and to send the image partition acquisition instruction to the image sensor.

[0251] The image partitioning acquisition instruction includes key area identifiers and redundant area identifiers in the preview image stream. The image partitioning acquisition instruction is used to instruct the image sensor to perform partitioned pixel merging acquisition of the key area indicated by the key area identifier in the preview image stream during video recording, and to perform at least one of the following: partitioned pixel merging acquisition of the redundant area indicated by the redundant area identifier in the preview image stream, and frame-by-frame reading of the pixels of the redundant area in the preview image stream.

[0252] In some embodiments of this application, the above-mentioned at least one reference temperature control strategy includes a cloud processing strategy, which migrates the task data of the task executed by the electronic device to the cloud device for processing; the fifth temperature change trend data corresponding to the cloud processing strategy is the temperature change trend data of the electronic device in the future second time period when the electronic device adopts the cloud processing strategy; the fifth temperature change trend data includes the fifth temperature value at multiple moments in the future second time period; the temperature control condition corresponding to the cloud processing strategy is: the fifth temperature value in the fifth temperature change trend data is less than the first threshold.

[0253] In some embodiments of this application, the target temperature control strategy is a cloud processing strategy, and the target object indicated by the target temperature control strategy is a cloud device; the processor 1010 is specifically used to generate a cloud migration instruction corresponding to the cloud processing strategy; and to send the cloud migration instruction to the cloud device.

[0254] The cloud migration instruction includes task data for the tasks performed by the electronic device; the cloud migration instruction is used to instruct the cloud device to process the task data and feed back the processed data to the electronic device.

[0255] The electronic device provided in this application embodiment uses a prediction unit to predict the future power consumption and temperature changes of the electronic device under specific task parameters based on currently collected temperature-related data and historically collected temperature-related data. Based on the prediction results, a temperature control strategy is adopted in advance to control the temperature, realizing a shift from "passive response" to "active prediction". Compared with cooling down the electronic device when it is already overheated, this solution can take a temperature control strategy in advance to control the temperature of the electronic device when it is predicted that it will overheat in the future. This can reduce the occurrence of overheating of the electronic device and eliminate the need for temperature control through operations such as frequency reduction, reduction of recording specifications, or direct interruption of the recording process. Thus, the temperature of the electronic device can be controlled without affecting the execution of the task.

[0256] It should be understood that, in this embodiment, the input unit 1004 may include a graphics processing unit (GPU) 10041 and a microphone 10042. The GPU 10041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1006 may include a display panel 10061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 1007 includes at least one of a touch panel 10071 and other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include a touch detection device and a touch controller. Other input devices 10072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here.

[0257] The memory 1009 can be used to store software programs and various data. The memory 1009 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1009 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1009 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0258] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into the processor 1010.

[0259] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described temperature control method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0260] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0261] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described temperature control method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0262] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0263] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the temperature control method embodiments described above, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0264] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0265] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0266] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A temperature control method, characterized in that, Applied to electronic devices, the method includes: Based on the currently collected temperature-related data and the historically collected temperature-related data, the prediction unit predicts the first temperature change trend data and the first load change trend data of the processor in the electronic device within the first time period in the future. The decision-making unit determines the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and sends an execution instruction to the target object indicated by the target temperature control strategy. The temperature-related data includes task parameters of the task executed by the electronic device, as well as temperature data and load data of the processor; the execution instruction is used to instruct the target object to execute the target temperature control strategy.

2. The method according to claim 1, characterized in that, The step of determining the target temperature control strategy through the decision-making unit based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data includes: Based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, the decision unit predicts at least one temperature change trend data corresponding to at least one reference temperature control strategy; wherein, the temperature change trend data corresponding to a reference temperature control strategy is the temperature change trend data of the electronic device in the future second time period when the reference temperature control strategy is adopted. If the target temperature change trend data meets the temperature control conditions, the reference temperature control strategy corresponding to the target temperature change trend data is determined as the target temperature control strategy; wherein, the temperature control conditions are the temperature control conditions corresponding to the reference temperature control strategy corresponding to the target temperature change trend data; and the target temperature change trend data is any one of the at least one temperature change trend data.

3. The method according to claim 2, characterized in that, The step of using a decision-making unit to predict at least one temperature change trend data corresponding to at least one reference temperature control strategy, based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, includes: The decision-making unit, based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and based on the priority of at least two reference temperature control strategies, predicts at least one temperature change trend data corresponding to at least one of the reference temperature control strategies.

4. The method according to claim 3, characterized in that, The at least two reference temperature control strategies include an active heat dissipation strategy, a thermal sensing task migration strategy, an image sensor load reduction strategy, and a cloud processing strategy; wherein, the priority of the at least two reference temperature control strategies from high to low is as follows: active heat dissipation strategy, thermal sensing task migration strategy, image sensor load reduction strategy, and cloud processing strategy.

5. The method according to any one of claims 2-4, characterized in that, The at least one reference temperature control strategy includes an active heat dissipation strategy, which is a strategy of adjusting the current of the heat dissipation device through the drive circuit in the electronic device. The second temperature change trend data corresponding to the active heat dissipation strategy is the temperature change trend data of the electronic device under different current levels within the future second time period when the active heat dissipation strategy is adopted. The second temperature change trend data includes the second temperature values ​​at multiple moments within the second future time period; The temperature control condition corresponding to the active heat dissipation strategy is: at at least one current setting, the second temperature value in the second temperature change trend data is less than the first threshold. The target temperature control strategy is the active heat dissipation strategy, and the target object indicated by the target temperature control strategy is the drive circuit. The step of sending an execution instruction to the target object indicated by the target temperature control strategy through the decision-making unit includes: The decision unit generates a current adjustment command corresponding to the active heat dissipation strategy; wherein the current adjustment command includes a target current level, and the target current level is the smallest current level among the at least one current level. The decision unit sends the current adjustment command to the drive circuit; wherein the current adjustment command is used to instruct the drive circuit to adjust the current of the heat dissipation device in the electronic device based on the target current level.

6. The method according to any one of claims 2-4, characterized in that, The at least one reference temperature control strategy includes a thermal sensing task migration strategy, which is a strategy to migrate a subtask of any processor to another processor for processing. The third temperature change trend data corresponding to the thermal sensing task migration strategy is the temperature change trend data of the electronic device within the future second time period when the electronic device adopts the thermal sensing task migration strategy and migrates different sub-tasks in the task. The third temperature change trend data includes the third temperature values ​​at multiple moments within the future second time period; The temperature control condition corresponding to the thermal sensing task migration strategy is: when migrating any subtask, the third temperature value in the third temperature change trend data is less than the first threshold. The target temperature control strategy is the thermal sensing task migration strategy, and the target object indicated by the target temperature control strategy is the thermal sensing task scheduler in the electronic device. The step of sending an execution instruction to the target object indicated by the target temperature control strategy through the decision-making unit includes: The decision-making unit generates a task migration instruction corresponding to the thermal sensing task migration strategy; wherein the task migration instruction includes a first processor identifier, a second processor identifier, and a task identifier. The decision unit sends the task migration instruction to the thermal sensing task scheduler; wherein the task migration instruction is used to instruct the thermal sensing task scheduler to migrate the subtask indicated by the task identifier from the processor indicated by the first processor identifier to the processor indicated by the second processor identifier for processing.

7. The method according to any one of claims 2-4, characterized in that, The electronic device performs a video recording task; the at least one reference temperature control strategy includes an image sensor load reduction strategy; the fourth temperature change trend data corresponding to the image sensor load reduction strategy is the temperature change trend data of the electronic device in the second time period in the future when the electronic device adopts the image sensor load reduction strategy. The fourth temperature change trend data includes the fourth temperature values ​​at multiple moments within the future second time period; The temperature control condition corresponding to the image sensor load reduction strategy is: the fourth temperature value in the fourth temperature change trend data is less than the first threshold. The target temperature control strategy is an image sensor load reduction strategy, and the target object indicated by the target temperature control strategy is the image sensor of the electronic device; the step of sending an execution instruction to the target object indicated by the target temperature control strategy through the decision unit includes: The decision unit generates an image partition acquisition instruction corresponding to the image sensor load reduction strategy; wherein, the image partition acquisition instruction includes key area identifiers and redundant area identifiers in the preview image stream; The decision unit sends the image partition acquisition instruction to the image sensor; wherein, the image partition acquisition instruction is used to instruct the image sensor to perform partition pixel merging acquisition of the key area indicated by the key area identifier in the preview image stream during video recording, and to perform at least one of the following: perform partition pixel merging acquisition of the redundant area indicated by the redundant area identifier in the preview image stream, and perform frame-by-frame reading of the pixels of the redundant area in the preview image stream.

8. The method according to any one of claims 2-4, characterized in that, The at least one reference temperature control strategy includes a cloud processing strategy, which is to migrate the task data of the task executed by the electronic device to the cloud device for processing; the fifth temperature change trend data corresponding to the cloud processing strategy is the temperature change trend data of the electronic device in the future second time period when the electronic device adopts the cloud processing strategy. The fifth temperature change trend data includes the fifth temperature values ​​at multiple moments within the future second time period; The temperature control condition corresponding to the cloud processing strategy is: the fifth temperature value in the fifth temperature change trend data is less than the first threshold. The target temperature control strategy is the cloud processing strategy, and the target object indicated by the target temperature control strategy is the cloud device; The step of sending an execution instruction to the target object indicated by the target temperature control strategy through the decision-making unit includes: The decision-making unit generates a cloud migration instruction corresponding to the cloud processing strategy; wherein the cloud migration instruction includes task data of the task executed by the electronic device. The decision-making unit sends the cloud migration instruction to the cloud device; wherein the cloud migration instruction is used to instruct the cloud device to process the task data and feed back the processed data to the electronic device.

9. A temperature control device, characterized in that, Applied to electronic devices, the device includes a prediction unit and a decision unit; The prediction unit is used to predict, based on the currently collected temperature-related data and the historically collected temperature-related data, the first temperature change trend data and the first load change trend data of the processor in the electronic device within a future first time period. The decision unit is used to determine the target temperature control strategy based on the currently collected temperature-related data, the first temperature change trend data, and the first load change trend data, and to send an execution instruction to the target object indicated by the target temperature control strategy. The temperature-related data includes task parameters of the task executed by the electronic device, as well as temperature data and load data of the processor; the execution instruction is used to instruct the target object to execute the target temperature control strategy.

10. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the temperature control method as described in any one of claims 1 to 8.

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