Electronic device control method, controller and refrigerator

Abstract

The invention relates to the technical field of refrigerators, in particular to an electronic device control method which is applied to a refrigerator with an electronic device and comprises the following steps that S101, reference time is obtained; s300, user activity information of the refrigerator is recorded based on the obtained reference time; s400, analyzing and processing the user activity information to determine at least one first control time period of the electronic device, wherein the refrigerator is used at a frequency lower than a first threshold value in the first control time period; and S500, when the current time is in the first control time period, the electronic device is controlled to operate at the first power lower than the set power of the electronic device. The invention further relates to a controller and a refrigerator. Through the embodiment of the invention, the continuous power consumption of electronic devices such as a proximity sensor is greatly reduced, the energy conservation of the whole refrigerator is realized, user intervention is not needed, the intelligent degree and the energy efficiency of the refrigerator are improved, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the technical field of refrigerators, specifically to an electronic device control method, a controller, and a refrigerator. Background Technology

[0002] With advancements in technology and improved living standards, refrigerators have become an indispensable appliance in modern households. Refrigerators not only preserve food and make ice, but also integrate increasingly sophisticated intelligent functions, such as touchscreen displays, automatic temperature control, and automatic defrosting, greatly enhancing the user experience. However, these additional intelligent functions typically require various sensors and control modules, most of which need to operate continuously to achieve real-time sensing and control, thus increasing the refrigerator's standby power consumption. Take the refrigerator's proximity sensor as an example. Its function is to detect the approach of a user, thereby controlling the opening of components such as the refrigerator's lights and display screen, and even the automatic opening of the refrigerator door. Traditional proximity sensors, especially radar-based proximity sensors, usually need to be constantly operational to be ready to detect human signals. However, users only approach the refrigerator for a small portion of the day; most of the time, no one is around the refrigerator, making the sensor's continuous operation a waste of energy. Studies have shown that for some smart refrigerators on the market, the power consumption of proximity sensors can account for about a quarter of the refrigerator's total standby power consumption excluding cooling, a considerable proportion. How to reduce the power consumption of electronic devices such as proximity sensors while ensuring their basic normal operation has become an urgent problem to be solved in order to improve the energy efficiency of refrigerators.

[0003] Therefore, there is still a real need for continued improvement in the electronic control aspects of refrigerators. Summary of the Invention

[0004] In view of this, the purpose of the embodiments of this application is to provide an improved electronic device control method, an improved controller, and an improved refrigerator, so as to overcome at least one of the above-mentioned disadvantages and / or other possible disadvantages not mentioned herein.

[0005] According to a first aspect of this application, an electronic device control method is provided, applied to a refrigerator with electronic devices. The electronic device control method includes the following steps: S101: acquiring a reference time; S300: recording user activity information of the refrigerator based on the acquired reference time; S400: analyzing and processing the user activity information to determine at least one first control time period for the electronic device, during which the refrigerator is used at a frequency lower than a first threshold; S500: controlling the electronic device to operate at a first power lower than its set power when the current time is within the first control time period. Thus, by acquiring the reference time record and analyzing user activity to determine the first control time period for the electronic device, the electronic device can reduce its operating power during this period due to the low usage frequency of the refrigerator, thereby significantly reducing the continuous power consumption of electronic devices such as proximity sensors and achieving energy saving for the entire refrigerator. Compared with existing technologies that require users to actively turn off electronic devices to reduce power consumption, the embodiments of this application can automatically achieve low-power operation of the electronic device while ensuring its basic normal function, without user intervention, thereby improving the user experience.

[0006] According to an optional embodiment, step S101 includes the following sub-steps: S100: acquiring environmental data around the refrigerator; S200: calculating the corresponding time based on the environmental data as the reference time. Thus, by using environmental data such as temperature, light intensity, or ambient sound to calculate the corresponding time as the reference time, a highly reliable reference time can still be calculated even when the refrigerator is offline and not connected to the network.

[0007] According to an optional embodiment, sub-step S200 includes the following sub-steps: S2100: acquiring environmental data for N consecutive sampling periods with a 24-hour sampling period, where N is an integer greater than one; S2200: determining at least one time point corresponding to the lowest value of environmental data within each sampling period; S2300: analyzing the relationship between the at least one time point corresponding to the lowest value of environmental data within each consecutive sampling period; S2400: calculating one of the time points as coordinate time T0 if the relationship between the time points in two adjacent sampling periods meets preset conditions. Thus, by utilizing the periodic changes in environmental data such as temperature, light intensity, or ambient sound throughout the day, a relatively accurate reference time can be obtained even when the refrigerator is offline and not connected to the network (at which point the refrigerator can run its internal clock, but cannot correspond to the actual time), providing a reliable time basis for subsequent recording and analysis of user activity information.

[0008] According to an optional embodiment, N=2, sub-step S200 further includes the following sub-steps: S2210: Determine the time point corresponding to the lowest environmental data value in the first sampling period as the first time point t1, and determine the time point corresponding to the lowest environmental data value in the second sampling period as the second time point t2; S2310: Determine whether the time interval between the first time point t1 and the second time point t2 meets the time threshold t0, which is preferably 24 hours ± 1 hour, and particularly preferably exactly 24 hours; S2410: Calculate the coordinate time T0 from the first time point t1 or the second time point t2. Thus, the steps for calculating the corresponding time based on environmental data from two sampling periods are further refined, resulting in highly reliable and easily calculated corresponding times.

[0009] According to an optional embodiment, N=3, sub-step S200 includes the following sub-steps: S2220: Determine the time point corresponding to the lowest environmental data value in the first sampling period as the first time point t1, determine the time point corresponding to the lowest environmental data value in the second sampling period as the second time point t2, and determine the time point corresponding to the lowest environmental data value in the third sampling period as the third time point t3; S2320: Determine whether the time intervals between the first time point t1 and the second time point t2, and between the second time point t2 and the third time point t3, both meet the time threshold t0, which is preferably 24 hours ± 1 hour, and particularly preferably exactly 24 hours; S2420: Calculate the coordinate time T0 from the first time point t1, the second time point t2, or the third time point t3. This more effectively avoids the influence of individual data deviations and further improves the accuracy of time calculation.

[0010] According to an optional embodiment, sub-step S200 further includes the following sub-steps: S2201: Determine the time points corresponding to the lowest values ​​of K environmental data within each sampling period, where K is a positive odd number greater than two, preferably K = 3; S2301: Determine whether the time intervals between the time points corresponding to the lowest values ​​of K environmental data in the first sampling period and the time points corresponding to the lowest values ​​of K environmental data in the second sampling period all meet the time threshold t0; S2401: Calculate the time point where the time points corresponding to the lowest values ​​of K environmental data in the second sampling period are exactly in the middle as the coordinate time T0. Thus, by using multiple lowest value points instead of relying solely on one lowest value point within each sampling period to calculate the corresponding time, the data becomes more complete and reliable, avoiding calculation errors caused by abnormal data at individual time points.

[0011] According to an optional embodiment, sub-step S200 further includes the following sub-steps: S2211: determining whether there is a data value within 12 hours before the time point corresponding to the highest environmental data value in each sampling period; S2221: determining the time points corresponding to the K lowest environmental data values ​​within 12 hours before the time point corresponding to the highest environmental data value in each sampling period. This effectively eliminates incomplete environmental data that may lead to incorrect time calculations.

[0012] According to an optional embodiment, in sub-step S100, the average value of environmental data for each hour is obtained. This can be achieved by recording environmental data values ​​every time interval t, and averaging the environmental data values ​​recorded within one hour. Here, t is 60 minutes / M, and M is an integer greater than one, preferably M = 10. This not only eliminates the influence of random factors but also fully utilizes the limited computing resources of the refrigerator controller, thereby improving analysis efficiency and providing a reliable data foundation for subsequent time estimation.

[0013] According to an optional embodiment, in step S300, user activity information for F consecutive cycles is recorded, where one recording cycle is 24 hours or 7×24 hours, and F is an integer greater than one, preferably an integer greater than ten. In step S400, based on the user activity information recorded in the F recording cycles, the first control time period for the user within a day or a week is determined through statistical analysis. Therefore, by recording and statistically analyzing multiple consecutive usage cycles, the distribution characteristics of the user's dependence on the refrigerator within a day or even a week can be accurately grasped, ensuring the reliability of the behavior analysis.

[0014] According to an optional embodiment, the electronic device control method further includes the following steps: S10: monitoring the network status of the refrigerator; S20: determining whether the refrigerator is in a network connected state; S220: if the refrigerator is in a network connected state, obtaining the network time as the reference time. This simplifies the process, provides high-quality time information for subsequent user activity analysis, and thus adapts to different application scenarios.

[0015] According to an optional embodiment, the electronic device control method further includes the following steps: S410: Analyzing and processing the user activity information, and determining H control time periods for the electronic device through an artificial intelligence algorithm, where H is an integer greater than one, wherein the frequency of use of the refrigerator increases sequentially from the first control time period to the Hth control time period and is lower than the corresponding frequency threshold; S510: When the current time is in the hth control time period of the H control time periods, controlling the electronic device to operate at a power lower than its set power, where h is an integer and 1≤h≤H, and the power of the hth control period increases with the increase of h. Thus, by adding multiple control time periods and corresponding graded power levels, more precise control of the operating power of the electronic device is achieved, ensuring optimal power during different usage frequency periods, reducing energy waste, achieving energy-saving goals while maximizing the normal operation of the electronic device, and improving the flexibility and practicality of the control strategy.

[0016] According to an optional embodiment, the electronic device control method further includes the following steps: S501: monitoring the current time; S502: determining whether the current time is within the first control time period; S503: controlling the electronic device to operate at a first power lower than its set power when the current time is within the first control time period; S504: controlling the electronic device to operate at its set power when the current time is not within the first control time period; S505: continuously monitoring whether the refrigerator is still being used at a frequency lower than a first threshold during the first control time period; if not, updating the first control time period determined in step S400. Thus, this dynamic monitoring and feedback mechanism ensures real-time synchronization between the control strategy and user needs, avoiding the impact of low-power operation on user use of the refrigerator.

[0017] According to one optional embodiment, the refrigerator includes a proximity sensor as part of the electronic device. This allows for a moderate reduction in the power consumption of the proximity sensor without affecting basic functionality, thereby reducing unnecessary energy consumption to some extent.

[0018] According to one optional embodiment, the environmental data includes ambient temperature data around the refrigerator. This allows for the effective use of the periodic variations in the ambient temperature data around the refrigerator to estimate time, providing a reliable basis for obtaining reference times and rationally planning low-power consumption periods.

[0019] According to a second aspect of this application, a controller is provided, including a memory, a processor, and a computer program stored in the memory, the processor being configured to execute the computer program to implement the electronic device control method provided according to any alternative embodiment of the first aspect above. Thus, this controller particularly possesses the advantages mentioned in the above embodiments.

[0020] According to a third aspect of this application, a refrigerator, particularly a household refrigerator, is provided, wherein the refrigerator includes a controller provided according to any alternative embodiment of the second aspect above and a proximity sensor at least signal-connected to the controller as the electronic device. Thus, this refrigerator, particularly a household refrigerator, possesses the advantages mentioned in the above embodiments. Attached Figure Description

[0021] The principles, features, and advantages of this application will be better understood below with reference to the accompanying drawings. The drawings include:

[0022] Figure 1 A schematic perspective view of a refrigerator according to an exemplary embodiment of this application is shown;

[0023] Figure 2 A schematic flowchart of an electronic device control method according to an exemplary embodiment of this application is shown;

[0024] Figure 3 A schematic flowchart of an electronic device control method according to an exemplary embodiment of this application is shown;

[0025] Figure 4 A schematic flowchart of sub-step S200 of an electronic device control method according to an exemplary embodiment of this application is shown;

[0026] Figure 5 A schematic flowchart of sub-step S200 of an electronic device control method according to an exemplary embodiment of this application is shown;

[0027] Figure 6 A schematic flowchart of sub-step S200 of an electronic device control method according to an exemplary embodiment of this application is shown;

[0028] Figure 7 A schematic flowchart of sub-step S200 of an electronic device control method according to an exemplary embodiment of this application is shown;

[0029] Figure 8 A schematic flowchart of sub-step S200 of an electronic device control method according to an exemplary embodiment of this application is shown;

[0030] Figure 9 A schematic flowchart of an electronic device control method according to an exemplary embodiment of this application is shown; and

[0031] Figure 10 A schematic flowchart of an electronic device control method according to an exemplary embodiment of this application is shown; and

[0032] Figure 11 A schematic flowchart of an electronic device control method according to an exemplary embodiment of this application is shown.

[0033] Figure label:

[0034] 1000: Electronic device control method; 2000: Refrigerator; 2100: Controller; 2001: Electronic device; 10: Proximity sensor. Detailed Implementation

[0035] To make the technical problems to be solved, the technical solutions, and the beneficial technical effects of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit the scope of protection of this application. Various embodiments may share the same view or multiple views for description, but not all features appearing in the same view should be interpreted as features that must be present in an embodiment.

[0036] For ease of understanding, the description provided in the background section of this application can be recalled. One objective of this application is to provide an electronic device control method applied to a refrigerator with electronic devices, wherein the electronic device control method includes the following steps: S101: acquiring a reference time; S300: recording user activity information of the refrigerator based on the acquired reference time; S400: analyzing and processing the user activity information to determine at least one first control time period for the electronic device, during which the refrigerator is used at a frequency lower than a first threshold; S500: controlling the electronic device to operate at a first power lower than its set power when the current time is within the first control time period. Thus, by recording and analyzing user activity through a reference time to determine the first control time period for the electronic device, the electronic device can reduce its operating power during this period due to the low frequency of refrigerator use, thereby significantly reducing the continuous power consumption of electronic devices such as proximity sensors and achieving energy saving for the entire refrigerator.

[0037] Exemplary embodiments of this application will now be described with reference to the accompanying drawings.

[0038] Figure 1 A schematic perspective view of a refrigerator 2000 according to an exemplary embodiment of this application is shown. Figure 1As shown, the refrigerator 2000 is specifically configured as a household refrigerator, which includes the controller 2100 and electronic device 2001 schematically illustrated herein. The controller 2100 may specifically include a memory, a processor, and a computer program stored on the memory. The processor is configured to execute the computer program to implement all the steps of the electronic device control method 1000 described below. Within the scope of this application, the computer program may be stored in a computer-readable storage medium. The computer-readable storage medium may include, for example, high-speed random access memory, and may also include non-volatile memory such as hard disks, RAM, plug-in hard disks, smart memory cards, secure digital cards, flash memory cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices. The processor may be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The memory, processor, and communication interface may be interconnected via a bus. Here, the refrigerator 2000 exemplarily includes a proximity sensor 10 as an electronic device 2001, which is at least signal-connected to the controller 2100 (schematically indicated by dotted lines). In embodiments not shown, the refrigerator 2000 may also include, for example, an automatic defrost sensor or a door open / close sensor as an electronic device 2001. These electronic devices 2001 typically have high power consumption characteristics, and their long-term, uninterrupted operation will significantly increase the overall energy consumption of the refrigerator.

[0039] Figure 2 A schematic flowchart of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. The electronic device control method 1000 can be applied, for example, to... Figure 1 The refrigerator 2000 shown has electronic components 2001. For example... Figure 2 As shown, the electronic device control method 1000 exemplarily includes steps S101, S300, S400 and S500.

[0040] In step S101, a reference time is obtained. Here, the reference time can be an accurate actual time (e.g., if the refrigerator 2000 is connected to the network), or it can be a virtual tag time (e.g., if the refrigerator 2000 is not connected to the network).

[0041] In step S300, user activity information of the refrigerator 2000 is recorded based on the acquired reference time. After acquiring the reference time, the controller 2100 further records user activity information of the refrigerator 2000 based on the reference time. User activity information can be obtained, for example, through various sensors of the refrigerator 2000. For example, a proximity sensor can record the number of times and duration of a user appearing around the refrigerator 2000, and a door opening / closing sensor can record the number of times and duration of the refrigerator door opening and closing. In a preferred embodiment, this step can record user activity information for F consecutive cycles, where one recording cycle is 24 hours or 7×24 hours, and F is an integer greater than one, preferably an integer greater than ten.

[0042] In step S400, the recorded user activity information is analyzed to determine at least one first control time period for the electronic device 2001, during which the refrigerator 2000 is used at a frequency below a first threshold. This indicates that the demand for the electronic device 2001 is low during the first control time period. The controller 2100 can accurately define at least one first control time period by statistically analyzing long-term user activity data to deduce the user's refrigerator usage patterns. For example, it can be determined that the user hardly uses the refrigerator 2000 during 01:00-04:00, 09:00-12:00, and 13:00-16:00 within a day, thereby defining these time periods as the first control time periods. Here, the first threshold can be exemplarily defined as the refrigerator 2000 being used only once every three consecutive hours. In a preferred embodiment, this step can determine the user's first control time period within a day or week by using statistical analysis methods based on the user activity information recorded in the aforementioned F recording cycles. Thus, by statistically analyzing user behavior habits through a large sample, results that closely approximate the user's actual usage patterns can be obtained. Especially when the amount of data is large (e.g., F > 10), it can cover users’ usage in different situations such as weekdays and weekends, making the statistical results more representative and better reflecting personalized usage patterns.

[0043] In step S500, when the current time falls within the first control time period, the electronic device 2001 is controlled to operate at a first power lower than its set power. Whenever the current time is detected to fall within the first control time period (e.g., 01:00-04:00, 09:00-12:00, and 13:00-16:00 in the example above), the controller 2100 controls the electronic device 2001 to operate at a power lower than its normal operating power. For example, the electronic device 2001 can be controlled to operate intermittently, waking up only every few seconds, instead of remaining constantly active. Taking a proximity sensor 10 configured as a radar sensor as the electronic device 2001 as an example, the set power can be, for example, transmitting one electromagnetic wave per second, with a power consumption of, for example, 0.6W; while the first power can be, for example, transmitting one electromagnetic wave every three seconds, with a power consumption of, for example, 0.2W. In this way, the power consumption of the electronic device 2001 can be effectively reduced during the first control time period, achieving energy saving.

[0044] Figure 3 A schematic flowchart of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 2 Based on the illustrated embodiment, step S101 can be further refined into sub-steps S100 and S200.

[0045] In sub-step S100, environmental data around the refrigerator 2000 is acquired. Here, the refrigerator 2000 can utilize its commonly equipped environmental sensors (such as temperature sensors, light intensity sensors, sound sensors, etc.) to collect various parameter data (such as corresponding temperature values, light intensity values, sound intensity values, etc.) of the environment in which the refrigerator 2000 is located, and transmit them to the refrigerator 2000's controller 2100. Preferably, this step involves acquiring the average environmental data for each hour. For example, environmental data values ​​are recorded every time interval t, and the average of the environmental data values ​​recorded within one hour is taken. Here, the time interval t is 60 minutes / M, and M is an integer greater than one. In a preferred embodiment, M = 10, that is, environmental data is collected every 6 minutes, 10 times per hour, and then the 10 collected values ​​are summed and averaged to obtain the average environmental data for that hour. On the one hand, according to statistical laws, this sample size is already quite accurate in estimating the population average. On the other hand, compared with continuous acquisition, interval acquisition can significantly reduce the power consumption of the sensors; by calculating the average value, the overall characteristics of the environmental parameters can be well reflected.

[0046] In sub-step S200, the corresponding time is calculated based on environmental data as a reference time. Here, since environmental parameters such as temperature and light intensity typically exhibit obvious periodic changes throughout the day, time information can be calculated by analyzing the change curves of these parameters. However, this time information exists only as a virtual label and does not need to completely correspond to the actual time. The specific calculation steps will be described in detail in the following embodiments.

[0047] Figure 4 A schematic flowchart of sub-step S200 of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Figure 4 As shown, sub-step S200 exemplarily includes secondary sub-steps S2100, S2200, S2300, S2400, and S2500.

[0048] In the second sub-step S2100, environmental data for N consecutive sampling periods are acquired, with N being an integer greater than one, using a 24-hour sampling period as one sampling cycle. Here, environmental data from multiple sampling periods will be used for comparative analysis.

[0049] In the second sub-step S2200, at least one time point corresponding to the lowest value of the environmental data within each sampling period is determined. Here, for each sampling period, the lowest value of the environmental data (e.g., temperature) is found (e.g., the lowest value is 'a' in the first sampling period and 'b' in the second sampling period), and then the time points at which they occur are determined (e.g., t1 and t2 respectively). a and t b Here, time point t a and t b At this point, it may still be impossible to accurately correspond to the actual time.

[0050] In the second sub-step S2300, the relationship between at least one time point corresponding to the lowest environmental data value within each consecutive sampling period is analyzed. Here, for example, the time points corresponding to the lowest environmental data values ​​of two or more consecutive sampling periods (e.g., time point t) can be compared. a and t b The interval between ).

[0051] In the second sub-step S2400, if the relationship between time points in two adjacent sampling periods meets preset conditions, one of the time points is calculated as coordinate time T0. Here, this coordinate time T0 is only a virtual time, that is, used as a label, not the actual time. This coordinate time T0 is preferably one to two hours before sunrise, for example, 4 or 5 a.m. a and t b If the interval between them meets the preset conditions, such as a difference of exactly 24 hours, then the time points t between these two time points can be calculated. aand t b This corresponds to the same moment, such as the nighttime period when the temperature is lowest. Therefore, time point t can be... a or t b The calculation is based on a preset coordinate time T0, such as 4 or 5 a.m. Generally speaking, one to two hours before sunrise, the refrigerator's environmental data, such as temperature, light, and noise, are at their lowest values ​​and change the least during the day. Therefore, using this as a reference time point to calculate other times yields the highest accuracy.

[0052] In the second sub-step S2500, the remaining time points of the 24 hours are calculated based on the coordinate time T0. For example, one hour after coordinate time T0 is calculated as T0+1, two hours after coordinate time T0 is calculated as T0+2, and so on, until T0+23 is calculated as all the time points of the 24 hours.

[0053] Figure 5 A schematic flowchart of sub-step S200 of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 4 Based on the embodiment shown, N=2, wherein the sub-steps S2200, S2300 and S2400 can be further refined into sub-steps S2210, S2310 and S2410.

[0054] In the second sub-step S2210, the time point corresponding to the lowest value of environmental data in the first sampling period is determined as the first time point t1, and the time point corresponding to the lowest value of environmental data in the second sampling period is determined as the second time point t2.

[0055] In the second sub-step S2310, it is determined whether the time interval between the first time point t1 and the second time point t2 meets the time threshold t0. Specifically, the time threshold t0 is preferably 24 hours ± 1 hour, that is, between 23 and 25 hours, and ideally exactly 24 hours. This is consistent with the cyclical change pattern of the surrounding environment within a day, thereby ensuring that the times corresponding to the lowest values ​​of the two compared data (such as the lowest temperature value) fall at the same time point on two consecutive days, making the time calculation more accurate and reliable.

[0056] In the second sub-step S2410, the first time point t1 or the second time point t2 is calculated as the coordinate time T0.

[0057] Here, this embodiment further provides a simplified time estimation scheme. First, environmental data for two days (N=2) is acquired, and the lowest data values ​​for those two days are recorded as t1 and t2 respectively (S2210). Then, it is determined whether the interval between t1 and t2 meets the threshold t0 (S2310). If yes, the corresponding coordinate time T0 for t1 or t2 can be estimated (S2410). If not, environmental data acquisition continues (S2100) until the time interval between the first time point t1 and the second time point t2 of two consecutive sampling periods meets the time threshold t0. Since this embodiment only requires collecting a small amount of data for analysis and comparison to estimate the time, the data volume is small and the calculation is simple, making it particularly suitable for occasions with limited computing resources.

[0058] Figure 6 A schematic flowchart of sub-step S200 of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 4 Based on the embodiment shown, N=3, wherein the sub-steps S2200, S2300 and S2400 can be further refined into sub-steps S2220, S2320 and S2420.

[0059] In the second sub-step S2220, the time point corresponding to the lowest environmental data value in the first sampling period is determined as the first time point t1, the time point corresponding to the lowest environmental data value in the second sampling period is determined as the second time point t2, and the time point corresponding to the lowest environmental data value in the third sampling period is determined as the third time point t3.

[0060] In the second sub-step S2320, it is determined whether the time intervals between the first time point t1 and the second time point t2, and between the second time point t2 and the third time point t3, both meet the time threshold t0. The time threshold t0 is preferably 24 hours ± 1 hour, and particularly preferably exactly 24 hours.

[0061] In the second sub-step S2420, the first time point t1, the second time point t2, or the third time point t3 is calculated as the coordinate time T0.

[0062] Here, this embodiment further provides a time extrapolation scheme using three days of data. By acquiring three days of environmental data (N=3), the lowest data values ​​for each of the three days are determined as t1, t2, and t3 (S2220). Then, it is determined whether the intervals between t1 and t2, and between t2 and t3, are all within the threshold t0, such as approximately 24 hours (S2320). If so, any one of t1, t2, and t3 is selected as the coordinate time T0 (S2420). If not, environmental data acquisition continues (S2100) until the intervals between t1 and t2, and between t2 and t3, for three consecutive sampling periods all meet the time threshold t0. Therefore, using three days of data allows for more comparative verification. If the changing trends of the three days' data all meet expectations, the periodicity is more pronounced. Furthermore, the horizontal comparison over three consecutive days effectively avoids the influence of individual data deviations, greatly improving the accuracy of the analysis results.

[0063] Figure 7 A schematic flowchart of sub-step S200 of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 5 Based on the illustrated embodiment, the sub-steps S2210, S2310 and S2410 can be further refined into sub-steps S2201, S2301 and S2401.

[0064] In the second sub-step S2201, the time points corresponding to the K lowest environmental data values ​​within each sampling period are determined, where K is a positive odd number greater than two. Specifically, K can be an odd number greater than 2, such as 3, 5, or 7, with 3 being the optimal value. The selection of three lowest value points is based on the following considerations: First, three points can form the minimum set of odd numbers required for multi-point matching; second, for example, environmental temperature data typically shows two to three distinct troughs within a day, and selecting three points can effectively cover these characteristic points; third, three points generate a smaller amount of data, and the matching calculation is not complex, making it easy to implement. Therefore, in most cases, using three points is a more ideal choice.

[0065] In the second sub-step S2301, it is determined whether the time intervals between the time points corresponding to the lowest values ​​of the K environmental data in the first sampling period and the time points corresponding to the lowest values ​​of the K environmental data in the second sampling period all meet the time threshold t0.

[0066] In the second sub-step S2401, the time point corresponding to the lowest value of K environmental data in the second sampling period is calculated as the coordinate time T0.

[0067] In the preferred embodiment where K=3, three minimum values ​​are determined from the daily data (S2201); then, it is determined whether the time points corresponding to the three minimum values ​​of the first day (e.g., t1a, t1b, and t1c) correspond one-to-one with the time points corresponding to the three minimum values ​​of the second day (e.g., t2a, t2b, and t2c), that is, whether the intervals between t1a and t2a, t1b and t2b, and t1c and t2c all meet the threshold t0 (S2301); if so, the middle time point corresponding to the three minimum values ​​of the second day (e.g., t2b located between t2a and t2c) is taken as the coordinate time T0 (S2401); if not, environmental data is continued to be acquired (S2100) until the intervals between t1a and t2a, t1b and t2b, and t1c and t2c all meet the threshold t0. Compared with single minimum value matching, the combination matching of multiple minimum values ​​can effectively reduce random interference and make time estimation more reliable.

[0068] Figure 8 A schematic flowchart of sub-step S200 of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 7 Based on the embodiment shown, the sub-step S2201 can be further refined into sub-steps S2211 and S2221.

[0069] In the second sub-step S2211, it is determined whether there is a data value within 12 hours before the time point corresponding to the highest value of environmental data in each sampling period.

[0070] In the second sub-step S2221, the time points corresponding to the K lowest environmental data values ​​within 12 hours before the time point corresponding to the highest environmental data value in each sampling period are determined.

[0071] This embodiment provides a method for determining whether sampled data completely covers the entire day. First, the highest environmental data value within a day is determined. Then, it is checked whether data exists for the preceding 12 hours (S2211). If so, the data coverage for the entire day is considered complete. Next, K lowest environmental data values ​​are determined within the 12 hours preceding the highest value (S2221) for subsequent calculations. Conversely, if the data is incomplete within 12 hours, sampling continues until the integrity requirement is met. This data integrity determination based on the highest value time can adapt to different sampling start times, eliminates the need for manually setting data ranges, and further improves the reliability of time-based calculations based on environmental parameters.

[0072] Figure 9 A schematic flowchart of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 3Based on the illustrated embodiment, the electronic device control method 1000 additionally includes steps S10, S20, and S220.

[0073] In step S10, the network status of refrigerator 2000 is monitored.

[0074] In step S20, it is determined whether the network status of the refrigerator 2000 is connected to the network.

[0075] In step S220, the network time is obtained as a reference time when the refrigerator 2000 is in a network-connected state.

[0076] Therefore, by monitoring the refrigerator's network status in real time, the time acquisition method can be adaptively selected, making full use of online resources, saving offline calculations, and making the process of obtaining reference time more flexible.

[0077] Figure 10 A schematic flowchart of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 3 Based on the illustrated embodiment, the electronic device control method 1000 exemplarily includes steps S410 and S510.

[0078] In step S410, user activity information is analyzed and processed. An artificial intelligence algorithm is used to determine H control time periods for the electronic device 2001, where H is an integer greater than one. From the first control time period to the Hth control time period, the frequency of use of the refrigerator 2000 increases sequentially and falls below the corresponding frequency threshold. Specifically, this step can employ a supervised learning paradigm from machine learning. First, the user activity information is divided into several time windows, each corresponding to a set of features (such as the number of times the door is opened within the time window, the duration of the door opening, etc.) and a label (such as high, medium, or low usage frequency of the refrigerator within the time window). Then, this dataset is used to train a predetermined artificial intelligence model, enabling it to predict the corresponding usage frequency label from the input time window features. Common machine learning models, including but not limited to, such as logistic regression, support vector machines, decision trees, random forests, and artificial neural networks, can be used. The model parameters are iteratively optimized to minimize the error between the predicted label and the true label until the model performance reaches the expected level. After training, the model is used to predict the usage frequency of the refrigerator within a continuous time window, thus obtaining the dynamic distribution of refrigerator usage frequency within a reference time period. Next, the time windows are sorted according to the predicted usage frequency and then divided into H control time periods. The time period with the lowest usage frequency is assigned to the first control time period, the time period with the highest usage frequency is assigned to the Hth control time period, and the rest are assigned to the second, third, and so on control time periods. Thus, the time-segmented usage pattern of the refrigerator is obtained through artificial intelligence algorithms. Taking a simple H=2 example, the user activity information is analyzed and processed, and the artificial intelligence algorithm derives two control time periods: the first control time period and the second control time period. In the first control time period, refrigerator 2000 is used at a frequency below a first threshold. In the second control time period, refrigerator 2000 is used at a frequency above the first threshold but below the second threshold, where the second threshold is higher than the first threshold. For example, the first threshold could be that refrigerator 2000 is used only once every three consecutive hours, and the second threshold could be that refrigerator 2000 is used only once every two consecutive hours.

[0079] In step S510, when the current time falls within the h-th control time period of H control time periods, the control electronic device 2001 operates at a power level lower than its set power level (h-th power), where h is an integer and 1 ≤ h ≤ H, and the h-th power level increases with increasing h. This means that in different control time periods, the operating power of the electronic device 2001 will be adjusted accordingly to the h-th level, and the power level is positively correlated with the frequency of refrigerator use during that time period. For example, in the first control time period when the refrigerator is used the least, the electronic device 2001 operates at the lowest first power; in the H-th control time period when the refrigerator is used the most, the electronic device 2001 operates at the highest H-th power; and in other control time periods, it operates at a power level between the two. In this way, the power consumption level of the electronic device 2001 can dynamically change with time periods and match the actual usage needs of the refrigerator, avoiding the problem of excessive or insufficient power in general energy-saving schemes, and maximizing user experience while reducing overall energy consumption. Taking a simple H=2 example, when the current time is within the second control time period, the control electronics 2001 operates at a second power lower than its set power, where the second power is higher than the first power. Taking the proximity sensor 10, constructed as a radar sensor, as the electronics 2001, the set power can be, for example, transmitting one electromagnetic wave per second, with a power consumption of, for example, 0.6W; the first power can be, for example, transmitting one electromagnetic wave every three seconds, with a power consumption of, for example, 0.2W; and the second power can be, for example, transmitting one electromagnetic wave every two seconds, with a power consumption of, for example, 0.3W.

[0080] Therefore, this embodiment further utilizes artificial intelligence technology to construct a future-oriented refrigerator usage prediction model by learning from historical user activity data, thereby obtaining a time-based power consumption control strategy that better meets users' personalized needs. Compared to static strategies, this dynamic control scheme can more accurately grasp the patterns of refrigerator usage and achieve real-time adaptive adjustment of electronic device power, thus having broader application prospects in the field of smart refrigerator energy saving.

[0081] Figure 11 A schematic flowchart of an electronic device control method 1000 according to an exemplary embodiment of this application is shown. Herein, Figure 3 Based on the illustrated embodiment, step S500 can be further refined into sub-steps S501, S502, S503, S504 and S505.

[0082] In sub-step S501, the current time is monitored.

[0083] In sub-step S502, it is determined whether the current time is within the first control time period.

[0084] In sub-step S503, when the current time is within the first control time period, the electronic device 2001 is controlled to operate at a first power lower than its set power.

[0085] In sub-step S504, when the current time is not within the first control time period, the electronic device 2001 is controlled to operate at its set power.

[0086] In sub-step S505, during the first control time period, it is continuously monitored whether the refrigerator 2000 is still being used at a frequency lower than the first threshold. Once it is detected that the frequency exceeds the threshold, it indicates that the actual usage does not conform to the preset pattern. At this time, the division of the first control time period determined based on historical data should be updated in a timely manner, that is, the first control time period determined in step S400 should be updated.

[0087] Therefore, by monitoring and dynamically adjusting in real time, the refrigerator's energy-saving operating mode can always be synchronized with the user's actual needs, improving energy efficiency while maximizing the user experience.

[0088] In other embodiments not shown in detail, the method steps and / or sub-steps and / or secondary sub-steps in the above figures can be combined with each other in a variety of ways, thereby achieving advantageous trade-offs in terms of computing resources, energy efficiency, and calculation accuracy.

[0089] Although specific embodiments have been described above, these embodiments are not intended to limit the scope of this application, even when only a single embodiment is described with respect to a particular feature. The feature examples provided in this application are intended to be illustrative and not limiting, unless explicitly stated otherwise. In practice, multiple features may be combined with each other as needed and where technically feasible. Various substitutions, modifications, and alterations are also conceived without departing from the spirit and scope of this application.

Claims

1. An electronic device control method (1000), applied to a refrigerator (2000) having electronic devices (2001), in, The electronic device control method (1000) includes the following steps: S101: Obtain reference time; S300: Record user activity information of the refrigerator (2000) based on the acquired reference time; S400: Analyze and process the user activity information to determine at least one first control time period of the electronic device (2001), during which the refrigerator (2000) is used at a frequency below a first threshold; S500: When the current time is within the first control time period, control the electronic device (2001) to operate at a first power lower than its set power.

2. The electronic device control method (1000) according to claim 1, wherein, Step S101 includes the following sub-steps: S100: Acquire environmental data around the refrigerator (2000); S200: Calculate the corresponding time based on the environmental data and use it as the reference time.

3. The electronic device control method (1000) according to claim 2, wherein, Sub-step S200 includes the following sub-steps: S2100: Acquire environmental data for N consecutive sampling periods with a 24-hour sampling period, where N is an integer greater than one; S2200: Determine at least one time point corresponding to the lowest value of environmental data within each sampling period; S2300: Analyze the relationship between at least one time point corresponding to the lowest value of environmental data within each consecutive sampling period; S2400: If the relationship between time points in two adjacent sampling periods meets the preset conditions, one of the time points will be calculated as coordinate time T0. S2500: Calculates the remaining time points in 24 hours based on coordinate time T0.

4. The electronic device control method (1000) according to claim 3, wherein, When N=2, sub-step S200 also includes the following sub-steps: S2210: The time point corresponding to the lowest value of environmental data in the first sampling period is determined as the first time point t1, and the time point corresponding to the lowest value of environmental data in the second sampling period is determined as the second time point t2. S2310: Determine whether the time interval between the first time point t1 and the second time point t2 meets the time threshold t0. The time threshold t0 is preferably 24 hours ± 1 hour, and more preferably exactly 24 hours. S2410: Calculate the coordinate time T0 from the first time point t1 or the second time point t2.

5. The electronic device control method (1000) according to claim 3, wherein, N=3, sub-step S200 includes the following sub-steps: S2220: The time point corresponding to the lowest value of environmental data in the first sampling period is determined as the first time point t1, the time point corresponding to the lowest value of environmental data in the second sampling period is determined as the second time point t2, and the time point corresponding to the lowest value of environmental data in the third sampling period is determined as the third time point t3. S2320: Determine whether the time intervals between the first time point t1 and the second time point t2, and between the second time point t2 and the third time point t3, both meet the time threshold t0. The time threshold t0 is preferably 24 hours ± 1 hour, and is particularly preferably exactly 24 hours. S2420: Calculate the coordinate time T0 from the first time point t1, the second time point t2, or the third time point t3.

6. The electronic device control method (1000) according to claim 4, wherein, Sub-step S200 also includes the following sub-steps: S2201: Determine the time point corresponding to the lowest value of K environmental data in each sampling period, where K is a positive odd number greater than two, preferably K = 3; S2301: Determine whether the time intervals between the time points corresponding to the lowest values ​​of the K environmental data in the first sampling period and the time points corresponding to the lowest values ​​of the K environmental data in the second sampling period all meet the time threshold t0. S2401: The time point in the middle corresponding to the lowest value of K environmental data in the second sampling period is used to calculate the coordinate time T0.

7. The electronic device control method (1000) according to claim 6, wherein, Sub-step S200 also includes the following sub-steps: S2211: Determine whether there is a data value within 12 hours before the time point corresponding to the highest value of environmental data in each sampling period; S2221: Determine the time points corresponding to the K lowest environmental data values ​​within 12 hours prior to the time point corresponding to the highest environmental data value in each sampling period.

8. The electronic device control method (1000) according to any one of claims 2 to 7, wherein, In sub-step S100, the average value of environmental data for each hour is obtained. For example, the environmental data value is recorded once every time period t, and the average value of the environmental data recorded within one hour is taken. Here, the time period t is 60 minutes / M, and M is an integer greater than one, preferably M=10.

9. The electronic device control method (1000) according to any one of claims 1 to 8, wherein, In step S300, user activity information for F consecutive cycles is recorded, wherein one recording cycle is 24 hours or 7×24 hours, and F is an integer greater than one, preferably an integer greater than ten. In step S400, based on the user activity information recorded in F recording cycles, the first control time period of the user within a day or a week is determined by statistical analysis.

10. The electronic device control method (1000) according to any one of claims 1 to 9, wherein, The electronic device control method (1000) further includes the following steps: S10: Monitor the network status of the refrigerator (2000); S20: Determine whether the network status of the refrigerator (2000) is connected to the network; S220: When the refrigerator (2000) is connected to the network, obtain the network time as the reference time.

11. The electronic device control method (1000) according to any one of claims 1 to 10, wherein, The electronic device control method (1000) further includes the following steps: S410: Analyze and process the user activity information, and determine H control time periods of the electronic device (2001) through artificial intelligence algorithm, where H is an integer greater than one. From the first control time period to the Hth control time period, the frequency of use of the refrigerator (2000) increases sequentially and falls below the corresponding frequency threshold. S510: When the current time is in the hth control time period of H control time periods, control the electronic device (2001) to operate at a power lower than its set power of h, where h is an integer and 1≤h≤H, and the power of h increases as h increases.

12. The electronic device control method (1000) according to any one of claims 1 to 11, wherein, The electronic device control method (1000) further includes the following steps: S501: Monitor the current time; S502: Determine whether the current time is within the first control time period; S503: When the current time is within the first control time period, control the electronic device (2001) to operate at a first power lower than its set power; S504: When the current time is not within the first control time period, control the electronic device (2001) to operate at its set power; S505: During the first control time period, continuously monitor whether the refrigerator (2000) is still being used at a frequency lower than the first threshold. If not, update the first control time period determined in step S400.

13. The electronic device control method (1000) according to any one of claims 2 to 12, wherein: The refrigerator (2000) includes a proximity sensor (10) as part of the electronic device (2001); and / or The environmental data includes the ambient temperature data around the refrigerator (2000).

14. A controller (2100) includes a memory, a processor, and a computer program stored in the memory, the processor being configured to execute the computer program to implement the electronic device control method (1000) according to any one of claims 1 to 13.

15. A refrigerator (2000), particularly a household refrigerator, wherein, The refrigerator (2000) includes: The controller (2100) according to claim 14; and A proximity sensor (10) that is at least signal-connected to the controller (2100) serves as the electronic device (2001).

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