A software upgrading method, air conditioner, electronic device, storage medium and program product

Abstract

The present disclosure relates to a software upgrading method, an air conditioner, an electronic device, a storage medium and a program product, and relates to the technical field of air conditioners. The method comprises: determining initial idle time prediction information of an air conditioner according to air conditioner operation history data and environmental parameter data; adjusting the initial idle time prediction information according to air conditioner operation control instructions and / or environmental parameter data; determining a target upgrading time period according to the adjusted initial idle time prediction information; and performing an upgrading operation of the air conditioner in the target upgrading time period. According to the present disclosure, the initial idle time prediction information is dynamically adjusted by collecting environmental parameter data and air conditioner operation control instructions in real time, which comprehensively reduces the user's perception of the air conditioner silent upgrading process, reduces the probability of the air conditioner silent upgrading process being interrupted, and comprehensively improves the reliability of the air conditioner silent upgrading and the user experience.

Description

Technical Field

[0001] This disclosure relates to the field of air conditioning technology, and more specifically, to a software upgrade method, an air conditioner, an electronic device, a storage medium, and a program product. Background Technology

[0002] Among related technologies, the rapid development of the Internet of Things (IoT) has greatly promoted the progress of the smart home field. Smart air conditioners, as a crucial component, are increasingly adopting remote control and Over-the-Air (OTA) upgrade technologies as industry standards. OTA technology allows air conditioning devices to remotely update firmware, thereby improving functionality, fixing vulnerabilities, and reducing the need for manual intervention. However, traditional OTA upgrade processes are often triggered at fixed times or randomly, easily disrupting users' daily use. Especially when upgrades are lengthy, they can cause temporary device unavailability, severely impacting the user experience. Summary of the Invention

[0003] To overcome the problems existing in related technologies, this disclosure provides a software upgrade method, an air conditioner, an electronic device, a storage medium, and a program product.

[0004] According to a first aspect of the present disclosure, a software upgrade method is provided, the software upgrade method comprising:

[0005] Based on historical air conditioner operation data and environmental parameter data, the initial idle time prediction information of the air conditioner is determined;

[0006] Adjust the initial idle time prediction information according to the air conditioning operation control command and / or the environmental parameter data;

[0007] Based on the adjusted idle time forecast information, the target upgrade time period is determined;

[0008] The air conditioner upgrade operation is performed during the target upgrade time period.

[0009] In some exemplary embodiments of this disclosure, the initial idle time prediction information includes idle time prediction scores corresponding to multiple time periods, and determining the target upgrade time period based on the adjusted idle time prediction information includes:

[0010] Obtain the estimated upgrade duration corresponding to the upgrade operation;

[0011] The target upgrade time period is determined based on the estimated upgrade duration and the idle prediction score corresponding to each time period.

[0012] In some exemplary embodiments of this disclosure, adjusting the initial idle time prediction information based on the air conditioning operation control command and / or the environmental parameter data includes:

[0013] A user behavior score is obtained based on the degree of consistency between the air conditioner operation control command and the initial idle time prediction information;

[0014] The user's intent is evaluated based on the environmental parameter data to obtain a user intent score;

[0015] Based on the user behavior score and user intent score, determine the predicted update score;

[0016] The initial idle time prediction information is adjusted based on the predicted updated score.

[0017] In some exemplary embodiments of this disclosure, obtaining the user behavior score based on the degree of conformity between the air conditioner operation control command and the initial idle time prediction information includes:

[0018] Determine whether the air conditioner operation control command matches the idle prediction score for the corresponding time period in the initial idle time prediction information;

[0019] In response to a discrepancy between the air conditioning operation control command and the idle time prediction score for the corresponding time period in the initial idle time prediction information, the user behavior score is determined based on the difference between the air conditioning operation control command and the initial idle time prediction information.

[0020] The air conditioning operation control commands include at least one of the following: start command, stop command, timer command, working mode setting command, and parameter adjustment command. The working mode setting command includes at least one of the following: heating command, cooling command, defrosting command, and air supply command.

[0021] In some exemplary embodiments of this disclosure, the step of evaluating the user's intent based on the environmental parameter data to obtain a user intent score includes:

[0022] In response to the environmental parameter data changing beyond a threshold, the user's intent is evaluated based on the environmental parameter data to obtain a user intent score.

[0023] The environmental parameter data includes at least one of temperature data, humidity data, and air quality data.

[0024] In some exemplary embodiments of this disclosure, adjusting the initial idle time prediction information based on the predicted update score includes:

[0025] Determine the prediction update score and idle prediction score for the corresponding time period;

[0026] The idle prediction score is adjusted based on the difference between the predicted update score and the idle prediction score.

[0027] In some exemplary embodiments of this disclosure, the software upgrade method further includes:

[0028] Determine the preset periodic trigger time;

[0029] The user behavior trigger time is determined based on the air conditioning operation control command;

[0030] Based on the periodic trigger time and / or user behavior trigger time, adjustments are made to the initial idle time prediction information.

[0031] In some exemplary embodiments of this disclosure, the software upgrade method further includes:

[0032] In response to receiving an interrupt upgrade operation command sent by the user and / or an interrupt upgrade operation command triggered locally by the air conditioner during the execution of the upgrade operation, the execution process of the upgrade operation is interrupted.

[0033] The interrupt upgrade operation command sent by the user includes at least one of a start command, a working mode setting command, and a parameter adjustment command, and the interrupt upgrade operation command triggered locally by the air conditioner includes at least one of a hardware interrupt command, a software interrupt command, and a self-test interrupt command.

[0034] In some exemplary embodiments of this disclosure, determining the target upgrade time period based on the adjusted idle time prediction information includes:

[0035] Based on the adjusted idle time forecast information, several candidate upgrade time periods were identified;

[0036] Based on the user's selected action, the target upgrade time period is determined from the plurality of candidate upgrade time periods.

[0037] According to a second aspect of the present disclosure, an air conditioner is provided, comprising: being capable of executing the software upgrade method described in any of the above technical solutions.

[0038] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the software upgrade method described in any of the preceding technical solutions.

[0039] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein when instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to perform the software upgrade method described in any of the above technical solutions.

[0040] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the software upgrade method as described in any of the above technical solutions.

[0041] The technical solutions provided by the embodiments of this disclosure may include the following beneficial effects:

[0042] The embodiments of this disclosure determine the initial idle time prediction information of the air conditioner based on historical air conditioner operation data and environmental parameter data. Based on user usage habits and the changing patterns of environmental parameter data, the silent period of the air conditioner can be determined. Based on this silent period, the initial prediction of the air conditioner upgrade period is completed, thus obtaining the aforementioned initial idle time prediction information. Furthermore, the initial idle time prediction information is adjusted according to air conditioner operation control commands and / or the environmental parameter data. The adjusted idle time prediction information not only reflects the user's usage needs based on the air conditioner operation control commands but also predicts the user's usage intentions based on environmental parameter data. Even further, based on the adjusted idle time prediction information, a target upgrade period is determined, and the air conditioner upgrade operation is performed during the target upgrade period. This comprehensively reduces the user's perception of the silent upgrade process and decreases the probability of interruption during the silent upgrade process, thereby reducing the time conflict between the user's air conditioner usage needs and the air conditioner software upgrade, and comprehensively improving the reliability of the silent upgrade and the user experience.

[0043] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0044] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0045] Figure 1 This is a flowchart illustrating a software upgrade method according to an exemplary embodiment of the present disclosure.

[0046] Figure 2 This is a flowchart illustrating a software upgrade method according to an exemplary embodiment of the present disclosure.

[0047] Figure 3 This is a flowchart illustrating a software upgrade scheme according to an exemplary embodiment of the present disclosure.

[0048] Figure 4 This is a block diagram illustrating an air conditioner according to an exemplary embodiment of the present disclosure.

[0049] Figure 5This is a schematic diagram illustrating an update time prediction table in a software upgrade method according to an exemplary embodiment of the present disclosure.

[0050] Figure 6 This is a schematic diagram illustrating an update time prediction table in a software upgrade method according to an exemplary embodiment of the present disclosure.

[0051] Figure 7 This is a schematic diagram illustrating an update time prediction table in a software upgrade method according to an exemplary embodiment of the present disclosure.

[0052] Figure 8 This is a schematic diagram illustrating an update time prediction table in a software upgrade method according to an exemplary embodiment of the present disclosure.

[0053] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure. Detailed Implementation

[0054] Exemplary embodiments of this disclosure will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. Various changes, modifications, and equivalents of the methods, apparatus, and / or systems described herein will become apparent upon understanding this disclosure. For example, the order of operations described herein is merely illustrative and is not limited to those orders set forth herein, but can be changed as will become apparent upon understanding this disclosure, except for operations that must be performed in a particular order. Furthermore, for clarity and brevity, descriptions of features known in the art may be omitted.

[0055] The embodiments described below, which are examples of some of the embodiments of this disclosure, do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0056] In related technologies, most existing silent software upgrade solutions rely on historical air conditioner operating data. If a user suddenly turns on the air conditioner, existing solutions cannot quickly adjust the upgrade plan, which may interrupt the upgrade process. This affects the smoothness and reliability of the silent software upgrade, and users will clearly perceive that the air conditioner is in an upgrade state, thus impacting the user experience. Therefore, a new software upgrade solution is urgently needed to reduce user awareness of the upgrade process and improve the smoothness of the silent software upgrade.

[0057] The steps of the method in the exemplary embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings and examples.

[0058] Figure 1 This is a flowchart illustrating a software upgrade method according to an exemplary embodiment of the present disclosure.

[0059] like Figure 1 As shown, in some embodiments, the software upgrade method of this disclosure includes:

[0060] In step S102, the initial idle time prediction information of the air conditioner is determined based on the air conditioner's historical operating data and environmental parameter data.

[0061] In one exemplary embodiment of this disclosure, the air conditioner operation history data typically includes the time when the air conditioner is turned on and off each time, as well as the working modes such as cooling, heating, dehumidification, and air supply. It also includes the air conditioner's fan speed and temperature settings for different time periods. Based on the air conditioner operation history data, the user's usage habits of the air conditioner can be determined.

[0062] In one exemplary embodiment of this disclosure, the environmental parameter data includes at least one of temperature data, humidity data, and air quality data.

[0063] In one exemplary embodiment of this disclosure, air quality data includes, but is not limited to, CO2 concentration, particulate matter concentration, and harmful gas concentration.

[0064] In one exemplary embodiment of this disclosure, the concentration of harmful gases includes, but is not limited to, HCHO (formaldehyde) concentration, TVOC (total volatile organic compounds) concentration, and ozone concentration.

[0065] In this embodiment of the disclosure, a machine model can be trained on historical data samples of air conditioner operation and environmental parameter data samples to learn users' usage habits of air conditioners. Then, in practical application scenarios, the machine model can be used to make a preliminary prediction of the idle time period of the air conditioner. The preliminary prediction result can include the idle time period and the probability that the air conditioner is idle during the idle time period.

[0066] In one exemplary embodiment of this disclosure, the control air conditioner prioritizes software upgrades during idle periods when the probability of being idle is highest.

[0067] In step S104, the initial idle time prediction information is adjusted according to the air conditioning operation control command and / or the environmental parameter data.

[0068] In one exemplary embodiment of this disclosure, the air conditioning operation control command includes operating status, operating mode, temperature setpoint, fan speed level, running time, and reservation information. The air conditioning operation control command may be determined based on an immediate command or a reservation command issued by the user. Based on the air conditioning operation control command, user behavior can be analyzed to determine whether the user has a need to use the air conditioning, but it is not limited to this.

[0069] In one exemplary embodiment of this disclosure, environmental parameter data may include, but is not limited to, brightness, humidity, indoor temperature and / or outdoor temperature. Since environmental parameter data is closely related to user needs, if it is determined based on the environmental parameter data that the indoor environment of the air conditioner does not meet the user's comfortable temperature range, it can be determined that the user is highly likely to have a temporary need for air conditioning. That is, the initial idle time prediction information can be adjusted based on the environmental parameter data to reduce the time conflict between the air conditioner upgrade period and the user's usage needs.

[0070] In an exemplary embodiment of this disclosure, air conditioning operation control commands and environmental parameter data can be used individually to adjust the initial idle time prediction information, or they can be combined to adjust the initial idle time prediction information. In particular, temporary air conditioning operation control commands and environmental parameter data detected before the software upgrade adjust the initial idle time prediction information so that the software upgrade scheme can adapt to temporary changes in usage needs.

[0071] In this embodiment of the disclosure, based on the initial idle time prediction information determined above, the air conditioning operation control commands and / or environmental parameter data collected before the upgrade are further combined to determine whether the user has a usage demand during the above-mentioned idle time period. When it is determined that the usage demand conflicts with any idle time period, the initial idle time prediction information is adjusted. For example, when the above-mentioned conflict is detected, the probability that all idle time periods are in an idle state is adjusted.

[0072] In step S106, the target upgrade time period is determined based on the adjusted idle time prediction information.

[0073] In this embodiment of the disclosure, the probability of idle time periods can be sorted according to the adjusted idle time prediction information. The idle time period with the highest probability of being idle can be determined as the target upgrade time period. That is, based on the initial prediction of idle time periods, the probability corresponding to the idle time periods is further adjusted according to the air conditioning operation control command and environmental parameter data, thereby determining the target upgrade time period.

[0074] In step S108, the air conditioner upgrade operation is performed during the target upgrade time period.

[0075] In this embodiment of the disclosure, the target upgrade period is determined based on steps S102, S104 and S106, and the air conditioner upgrade operation is performed during the target upgrade period. This comprehensively reduces the user's perception of the silent upgrade process of the air conditioner and also reduces the probability of the silent upgrade process being interrupted, thereby comprehensively improving the reliability of the silent upgrade of the air conditioner and the user experience.

[0076] In one exemplary embodiment of this disclosure, in Figure 1 Based on the example shown, the idle time prediction information includes idle prediction scores corresponding to multiple time periods. Determining the target upgrade time period based on the adjusted idle time prediction information includes: determining the target upgrade time period based on the idle prediction scores corresponding to each time period.

[0077] In this embodiment of the disclosure, Figure 5 The idle time prediction information includes a schematic diagram of a summary table of multiple time periods mentioned above. The summary table may include the current air conditioner status, the current indoor environment, the predicted temperature of the region, the OTA predicted upgrade time, and the prediction time score. The prediction time score corresponds to the priority of upgrading the air conditioner during the idle time period, but is not limited to this.

[0078] Specifically, such as Figure 5 As shown, the current indoor temperature is 26℃, and the air conditioner is off. Based on user habits (air conditioner is used from 9:00 to 22:00), the model generates a time prediction table, i.e., score table 500. The score table includes, but is not limited to, the current air conditioner status, the current indoor temperature, the predicted temperature for the region, the predicted OTA upgrade time, and the predicted time score. Based on the predicted time score in score table 500, 01:01 can be determined as the target upgrade time period.

[0079] In one exemplary embodiment of this disclosure, in Figure 1 Based on the example shown, determining the target upgrade time period according to the idle prediction score corresponding to each time period includes: obtaining the estimated upgrade duration corresponding to the upgrade operation; and determining the target upgrade time period according to the estimated upgrade duration and the idle prediction score corresponding to each time period.

[0080] In this embodiment of the disclosure, after determining the aforementioned time period, the estimated upgrade duration of the air conditioner can be determined by combining the network communication status corresponding to the time period. That is, different time periods correspond to different estimated upgrade durations. On the one hand, it is necessary to ensure that the duration of the time period is longer than the estimated upgrade duration, and to avoid one upgrade process covering multiple time periods as much as possible, so as to reduce data conflicts between multiple time periods. On the other hand, prioritizing the selection of time periods with shorter estimated upgrade durations is beneficial to further reduce the user's perception of the air conditioner upgrade process, improve the utilization rate of network resources during off-peak hours, and also improve the reliability of the software upgrade scheme.

[0081] In an exemplary embodiment of this disclosure, the various time periods can also be sorted or filtered according to the estimated upgrade duration of the air conditioner. For example, if the estimated upgrade duration of the first time period is 10 minutes, the estimated upgrade duration of the second time period is 20 minutes, and the estimated upgrade duration of the third time period is 40 minutes, then when determining the first time period as the target upgrade time period based on the estimated upgrade duration and the idle prediction score corresponding to each time period, the first time period is preferentially determined as the target upgrade time period.

[0082] In this embodiment of the disclosure, by combining the above-mentioned estimated upgrade duration and the idle prediction score corresponding to each time period, the time period with a shorter estimated upgrade duration and a higher idle prediction score is selected as the target time period, so that the air conditioner can be silently upgraded in a shorter time period with a lower probability of being used by the user, thereby comprehensively improving the reliability of silent upgrade and user experience.

[0083] Figure 2 This is a flowchart of a first software upgrade method illustrated according to an exemplary embodiment of the present disclosure. Figure 1 .

[0084] like Figure 2 As shown, in Figure 1 Based on the software upgrade method shown, step S104 may include the following steps.

[0085] In step S202, a user behavior score is obtained based on the degree of conformity between the air conditioner operation control command and the initial idle time prediction information.

[0086] In this embodiment of the disclosure, the user's demand for air conditioning can be detected based on the air conditioning operation control command. If the time period in which the demand for air conditioning is determined to be used overlaps with any time period in the initial idle time prediction information, it is determined that the air conditioning operation control command and the idle time prediction information do not meet the requirements for silent upgrade. Time periods in which there is no overlap are considered to meet the requirements for silent upgrade. Based on this, a user behavior score is obtained, which can be recorded as CompIUsage during the calculation process.

[0087] In one exemplary embodiment of this disclosure, the air conditioner operation control command includes at least one of a start command, a stop command, a timer command, a working mode setting command, and a parameter adjustment command, wherein the working mode setting command includes at least one of a heating command, a cooling command, a defrosting command, and a fan command.

[0088] In one exemplary embodiment of this disclosure, user actions that interrupt or skip the upgrade during each software upgrade process are recorded as correction factors for the next user behavior score.

[0089] In one exemplary embodiment of this disclosure, the optimal time is selected based on the user's current usage and the predicted idle time period. The control behavior is defined as a = (OTA_time), where OTA_time is the predicted upgrade time period.

[0090] In one exemplary embodiment of this disclosure, the user behavior score after execution in each time period is determined based on the actual state of the air conditioner and the fluctuation of the ambient temperature, reflecting the suitability of performing a silent software upgrade during that time period. For example, if an OTA upgrade is performed when the user is not using the air conditioner, the score obtained is positive; if the upgrade is triggered when the user is using the air conditioner, the score is negative.

[0091] In step S204, the user's intention is evaluated based on the environmental parameter data to obtain a user intention score, which can be denoted as CompIEnv during the calculation process.

[0092] In one exemplary embodiment of this disclosure, the environmental parameter data includes at least one of temperature data, humidity data, and air quality data.

[0093] In this embodiment of the disclosure, by quantifying environmental parameter data and determining whether it leads to a temporary intention for the user to use the software during the upgrade process, the probability of silent upgrade being interrupted due to the user using air conditioning in response to a sudden change in the environment is reduced.

[0094] For example, when the outdoor temperature is too high (e.g., above 30°C) or too low (e.g., below 5°C), users are more likely to turn on the air conditioner for cooling or heating, and the corresponding user intent score can be higher; while at a suitable temperature (e.g., 15-25°C), users are less likely to turn on the air conditioner, and the user intent score is lower accordingly.

[0095] For example, when the indoor humidity is too high (e.g., exceeding 70%), users may intend to turn on the dehumidification mode or use the air conditioner to assist in dehumidification, and the user intention score can be appropriately increased; when the humidity is within the normal range (40%-60%), it has little impact on the user's intention, and the user intention score is moderate.

[0096] In step S206, a predicted update score is determined based on the user behavior score and the user intent score.

[0097] In this embodiment of the disclosure, the user's current usage intent and environmental changes are monitored in real time, and a predicted update score is determined based on the user behavior score and user intent score. Then, based on the predicted update score, it is used to concretely determine whether the time period in the user behavior score and user intent score is suitable for OTA silent upgrade.

[0098] In an exemplary embodiment of this disclosure, the idle time prediction information is used to calculate the score of each time period, i.e., the idle prediction score r(s,a) = CompIUsage + CompIEnv, where CompIUsage is the evaluation of whether the user behavior matches the prediction, i.e., the user behavior score, and CompIEnv is the matching degree between the current ambient temperature and the user's intention, i.e., the user intention score.

[0099] In step S208, the initial idle time prediction information is adjusted based on the predicted update score.

[0100] In this embodiment of the disclosure, the predicted update score is determined by real-time monitoring of environmental parameter data and air conditioning operation control commands. That is, by updating the score of the time period in the idle time prediction information, the probability of interruption and skipping of the air conditioning upgrade period due to temporary usage demand caused by changes in environmental parameter data and / or air conditioning operation control commands is reduced. This reduces the user's perception of the silent air conditioning upgrade process and improves the reliability and continuity of the silent air conditioning upgrade.

[0101] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2 Based on the example shown, the process of obtaining a user behavior score based on the consistency between the air conditioner operation control command and the initial idle time prediction information includes:

[0102] Determine whether the air conditioner operation control command matches the idle prediction score for the corresponding time period in the initial idle time prediction information;

[0103] In response to a discrepancy between the air conditioning operation control command and the idle prediction score for the corresponding time period in the initial idle time prediction information, the user behavior score is determined based on the difference between the air conditioning operation control command and the initial idle time prediction information.

[0104] In this embodiment of the disclosure, in response to the discrepancy between the air conditioner operation control command and the idle prediction score of the corresponding time period in the initial idle time prediction information, that is, based on the air conditioner operation control command reflecting the user's usage needs and the idle prediction score of the time period, the user behavior score is obtained to update the above idle prediction score, so as to reduce the time conflict between the air conditioner silent upgrade and the user's usage needs.

[0105] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2Based on the example shown, the step of evaluating the user's intention based on the environmental parameter data to obtain a user intention score includes: in response to the change value of the environmental parameter data exceeding a change threshold, evaluating the user's intention based on the environmental parameter data to obtain the user intention score.

[0106] In this embodiment of the disclosure, changes in environmental parameter data exceeding a certain threshold often indicate a significant change in the user's environment, which may affect the user's demand for air conditioning. By assessing user intent at this time, the potential usage intent of the user due to environmental changes can be captured more accurately, allowing for timely responses and the provision of services that better meet the user's actual needs.

[0107] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2 Based on the example shown, the software upgrade method further includes: determining the predicted update score and the idle prediction score for the corresponding time period; and adjusting the idle prediction score according to the difference between the predicted update score and the idle prediction score.

[0108] In this embodiment of the disclosure, the expression for adjusting the idle prediction score based on the difference between the predicted update score and the idle prediction score is Q(s, a)←Q(s, a)'+α[r(s, a)-Q(s, a)'], where s is the environmental state, and the environmental state s=(O, T I T O The current on / off status of the air conditioner (O) and the current indoor temperature (T) are used to determine the air conditioner's status. I Current ambient temperature T O The calculation determines that Q(s,a)' is the initial score of the time period before adjustment, r(s,a) is the predicted updated score mentioned above, Q(s,a) is the idle predicted score of the time period after adjustment, and α is the learning rate. By combining the results of the initial score and the current score, the scoring model for the next OTA upgrade can be updated, so that the time period with the higher score is given priority as the candidate for OTA upgrade.

[0109] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2 Based on the example shown, the software upgrade method further includes: determining a preset periodic trigger time; determining a user behavior trigger time according to the air conditioner operation control command; and triggering an adjustment to the initial idle time prediction information according to the periodic trigger time and / or the user behavior trigger time.

[0110] In this embodiment, by pre-setting a periodic trigger time, the initial idle time prediction information can be adjusted periodically according to the latest air conditioner operation control commands to adapt to the changing patterns of user air conditioner usage in different seasons and time periods. Adjusting based on user behavior trigger time allows for timely response to individual users' special usage habits or temporary changes. For example, users typically use the air conditioner on weekends or holidays differently than on weekdays; periodic triggering can capture this regular time variation pattern. If a user uses the air conditioner earlier or later for special reasons, the user behavior trigger time can promptly capture this special situation, thus making the predicted idle time period closer to the user's actual usage and improving the accuracy of predicting the silent upgrade period.

[0111] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2 Based on the example shown, the software upgrade method further includes: in response to receiving an interrupt upgrade operation instruction sent by a user and / or an interrupt upgrade operation instruction triggered locally by the air conditioner during the execution of the upgrade operation, interrupting the execution of the upgrade operation.

[0112] In an exemplary embodiment of this disclosure, the interrupt upgrade operation instruction sent by the user includes at least one of a start instruction, a working mode setting instruction, and a parameter adjustment instruction, and the interrupt upgrade operation instruction triggered locally by the air conditioner includes at least one of a hardware interrupt instruction, a software interrupt instruction, and a self-test interrupt instruction.

[0113] In one exemplary embodiment of this disclosure, the hardware interrupt instruction may be an instruction determined based on a power-off signal or an overshoot protection instruction.

[0114] In one exemplary embodiment of this disclosure, the software interruption instruction may be an instruction generated based on software execution or an instruction sent by a server received by the software.

[0115] In one exemplary embodiment of this disclosure, the self-test interruption command may be a quality generated during the operation of the air conditioner based on a detected operational fault for self-protection.

[0116] In this embodiment of the disclosure, in response to receiving an interrupt upgrade operation instruction during the execution of the upgrade operation, the execution process of the upgrade operation is interrupted. In particular, if the user needs to use a specific function of the air conditioner to cope with sudden environmental changes, the upgrade operation may temporarily disable the function. Interrupting the upgrade allows the user to use the required function in a timely manner and adapt to various complex and ever-changing usage scenarios.

[0117] In one exemplary embodiment of this disclosure, in Figure 1 and Figure 2Based on the example shown, determining the target upgrade time period according to the adjusted idle time prediction information includes: determining multiple candidate upgrade time periods based on the adjusted idle time prediction information; and determining the target upgrade time period from the multiple candidate upgrade time periods based on the user's selection operation.

[0118] In this embodiment, the selection of upgrade time periods is determined based on adjusted idle time prediction information, minimizing disruption to users' air conditioning use during the upgrade process. Since the selected time periods are unlikely to be used, the upgrade can be completed without disturbing users, ensuring continuity and comfort for their air conditioning use. For air conditioning system administrators, this approach helps to rationally allocate system resources. Upgrades can be performed in batches during specific time periods based on the idle time and upgrade needs of multiple users, improving the utilization efficiency of server and network resources and reducing upgrade costs and impact on overall system performance. Furthermore, upgrading during air conditioning idle periods reduces the possibility of upgrade failures due to other operations or tasks occupying system resources. Simultaneously, users can make upgrade selections in a relatively quiet and undisturbed environment, allowing for more careful consideration and operation, reducing the probability of upgrade problems caused by misoperation, thereby improving the success rate and reliability of software upgrades.

[0119] Figure 3 This is a flowchart illustrating a software upgrade scheme according to an exemplary embodiment of the present disclosure.

[0120] like Figure 3 As shown, an exemplary embodiment of this disclosure illustrates a software upgrade scheme including the following:

[0121] Environmental status acquisition phase S302: Acquire sensor information such as indoor temperature, ambient temperature, and air conditioning status, but not limited to these.

[0122] Model prediction phase S304: Initial prediction and behavior selection, and prediction and scoring of appropriate OTA upgrade time periods based on air conditioning operation history data.

[0123] OTA upgrade control phase S306: Perform OTA upgrades within the target time period and obtain user behavior evaluations.

[0124] Feedback and Optimization Phase S308: After the upgrade is completed, the system will check whether the upgrade was successful and update the behavior prediction model by combining user behavior feedback and air conditioner operation history data to make future predictions more accurate.

[0125] The OTA upgrade control phase S306 also includes the following steps:

[0126] Step S310: Check if the user uses the service during the predicted time period. If usage is detected, re-evaluate and adjust the time.

[0127] Step S312: Perform OTA upgrade. If the conditions are met, perform a silent upgrade according to the predicted time; otherwise, postpone the upgrade and wait for a new opportunity.

[0128] Figure 4 This is a block diagram illustrating an air conditioner according to an exemplary embodiment of the present disclosure.

[0129] like Figure 4 As shown, the air conditioner 400 can perform the software upgrade method as shown in any of the above technical solutions, which may specifically include: a historical data acquisition module 402, a real-time user behavior monitoring module 404, an upgrade management module 406, a firmware upgrade module 408, and a user interaction module 410.

[0130] The functions of the historical data acquisition module 402 include: collecting and storing historical usage data of the air conditioner over a long period of time, including the on / off time and off duration of the air conditioner. This data is used to predict the time period in the future when a silent upgrade may be appropriate, providing additional reference for the system.

[0131] In one exemplary embodiment of this disclosure, the historical data acquisition module 402 interacts with the system's database to store and manage historical usage data. The upgrade management module 406 uses this data to help select a potentially suitable time period for the upgrade.

[0132] For example, the historical data acquisition module 402 collected data showing that the regional air conditioner runs for an average of 18 hours per day in summer and only 2 hours per day in winter. The upgrade management module 406 initially predicted that a major version upgrade would be pushed out in winter and only security patches would be installed in summer.

[0133] For example, the historical data acquisition module 402 collected data showing that user C had enabled sleep mode at 22:00 for three consecutive days. The upgrade management module 406 initially predicted to avoid the 22:00-6:00 time period and choose to upgrade during the daytime.

[0134] The functions of the real-time user behavior monitoring module 404 include: real-time monitoring of user behavior and air conditioner usage status, ensuring that the system can know at any time whether the air conditioner is being used, whether the user actively starts the air conditioner, or whether a silent upgrade operation is needed when the air conditioner is turned off.

[0135] In an exemplary embodiment of this disclosure, the real-time user behavior monitoring module 404 obtains the status information of the air conditioner in real time through direct interaction with the air conditioner's sensors and control system, and transmits the data to the upgrade management module as a basis for decision-making.

[0136] For example, active use, idle status, and interruption prediction can be detected based on air conditioner operation control commands. An active status can be defined as the air conditioner being in operation and having user interaction within the last 5 minutes. An idle status can be defined as the air conditioner being off or running continuously without user operation. The time when a user is likely to turn on the air conditioner can be determined based on the user's usual home arrival time, which means interruption prediction for air conditioner upgrades can be performed.

[0137] The upgrade management module 406 is the core module of the entire system. It is responsible for dynamically selecting the most suitable time period to perform silent upgrade tasks by combining historical and real-time air conditioner operation data. It can interrupt the current upgrade while the user is using the air conditioner and reselect the optimal upgrade time period based on new real-time data to ensure an uninterrupted user experience.

[0138] In one exemplary embodiment of this disclosure, the upgrade management module 406 engages in bidirectional data interaction with the air conditioner operation history data acquisition module and the real-time user behavior monitoring module to obtain relevant data for making upgrade decisions. During upgrade execution, it works in conjunction with the firmware upgrade module to ensure the upgrade task proceeds smoothly or is interrupted in a timely manner.

[0139] After the air conditioner operation history data acquisition module 402 determines the predicted idle time period, the upgrade management module 406, in conjunction with the real-time status monitoring collected by the real-time user behavior monitoring module 404, dynamically selects the optimal silent upgrade time window to ensure that the upgrade process does not affect the user's normal use.

[0140] The firmware upgrade module 408 is responsible for executing the firmware upgrade operation of the air conditioner. Based on the time window provided by the upgrade management module, this module initiates and completes the silent firmware upgrade task. If an interruption command is received during the upgrade process, the firmware upgrade module will pause the upgrade and save the current progress so that it can continue the upgrade at an appropriate time.

[0141] In one exemplary embodiment of this disclosure, the firmware upgrade module 408 interacts directly with the upgrade management module to ensure that the upgrade task is executed smoothly according to the system plan, while also being able to flexibly respond to interruption requests.

[0142] User interaction module 410 is an optional module. Its functions include: providing additional flexibility to allow users to interact with the system through the APP or other devices; users can choose the priority upgrade time, confirm whether to perform the upgrade immediately, or check the upgrade progress.

[0143] In one exemplary embodiment of this disclosure, the user interaction module 410 interacts with the user device to transmit user settings, provide notifications, and display system upgrade status, thereby improving user experience and system transparency.

[0144] In one exemplary embodiment of this disclosure, the user interaction module 410 can be used by the user to select an idle time period.

[0145] In one exemplary embodiment of this disclosure, the user interaction module 410 can receive user feedback on the silent upgrade scheme.

[0146] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0147] The following is combined Figures 5 to 8 As shown, this paper further explains how to adjust the OTA upgrade time in the software upgrade scheme disclosed herein.

[0148] like Figure 5 As shown, environmental parameter data is detected, including the current indoor ambient temperature of 26℃ and the air conditioner status of being off. Based on the air conditioner's historical operation data, it is determined that the user's usage habit is to use the air conditioner from 9:00 to 22:00. Other time periods are predicted as the air conditioner's idle time periods. The environmental parameter data and the air conditioner's historical operation data are input into the machine model to generate initial idle time prediction information. The initial idle time prediction information includes a time prediction table, i.e., a scoring table. The scoring table also includes the current air conditioner status, the current indoor temperature, the predicted temperature of the region, the predicted OTA upgrade time, and the predicted time score, etc., but is not limited to these.

[0149] like Figure 5 As shown, a score is assigned to each time interval (1 minute interval), and a time prediction table 500 is generated. The time with the best score is selected as the target upgrade period, which is the time for the air conditioner's OTA upgrade. At this time, the start time of the predicted OTA upgrade time is 1:01 PM.

[0150] like Figure 6 As shown, based on environmental parameter data, the ambient temperature is determined to drop to 23℃ at 22:20 (the possibility of users using air conditioning may increase). Therefore, the environmental parameter data... Figure 5 The start time of the identified target upgrade period, 1:01, generated negative feedback, for example, regarding... Figure 5 All predicted times are scored -1, and a new time prediction table of 600 is obtained. The best upgrade time is updated to 1:04.

[0151] like Figure 7 As shown, based on the air conditioner operation control command, it was determined that the user's power-on behavior was detected at 23:00. This will also negatively affect the time of 1:04. This update is necessary. Figure 6 The predicted time scores in the time prediction table shown, for example, for Figure 6All predicted times are scored -1, and the time with the highest score, 02:01, is selected as the upgrade time, which is the starting point of the target upgrade period.

[0152] In addition, the air conditioner controller can update the evaluation of the behavior based on the evaluations previously obtained and the current evaluations, and use the time with the highest evaluation as the optimal upgrade time to obtain the current time prediction evaluation table 700.

[0153] like Figure 8 As shown, the machine model continuously updates the initial idle time prediction information after learning the air conditioning operation control commands and environmental parameter data over a period of time. The current time prediction evaluation table 800 shows that the time period starting from 2:04 has the highest upgrade evaluation, so an OTA upgrade is performed at that time.

[0154] In this embodiment of the disclosure, the air conditioner's silent upgrade is optimized based on real-time user behavior. The air conditioner's control system dynamically selects the OTA upgrade time through feedback and scoring updates of user behavior data.

[0155] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure. For example, device 900 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc.

[0156] Reference Figure 9 The device 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0157] Processing component 902 typically controls the overall operation of device 900, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 902 may include one or more processors 920 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 902 may include one or more modules to facilitate interaction between processing component 902 and other components. For example, processing component 902 may include a multimedia module to facilitate interaction between multimedia component 908 and processing component 902.

[0158] Memory 904 is configured to store various types of data to support the operation of device 900. Examples of this data include instructions for any application or method operating on device 900, contact data, phonebook data, messages, pictures, videos, etc. Memory 904 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0159] Power supply component 906 provides power to various components of device 900. Power supply component 906 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 900.

[0160] Multimedia component 908 includes a screen that provides an output interface between the device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 908 includes a front-facing camera and / or a rear-facing camera. When the device 900 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0161] Audio component 910 is configured to output and / or input audio signals. For example, audio component 910 includes a microphone (MIC) configured to receive external audio signals when device 900 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 904 or transmitted via communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

[0162] I / O interface 912 provides an interface between processing component 902 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0163] Sensor assembly 914 includes one or more sensors for providing status assessments of various aspects of device 900. For example, sensor assembly 914 may detect the on / off state of device 900, the relative positioning of components such as the display and keypad of device 900, changes in position of device 900 or a component of device 900, the presence or absence of user contact with device 900, orientation or acceleration / deceleration of device 900, and temperature changes of device 900. Sensor assembly 914 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 914 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0164] Communication component 916 is configured to facilitate wired or wireless communication between device 900 and other devices. Device 900 can access wireless networks based on communication standards, such as WiFi, 3G, 4G, 9G, other communication standards, or combinations thereof. In some embodiments of this disclosure, communication component 916 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In some embodiments of this disclosure, communication component 916 further includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0165] In some embodiments of this disclosure, the apparatus 900 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0166] In some embodiments of this disclosure, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 904 including instructions that can be executed by a processor 920 of device 900 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0167] In some embodiments of this disclosure, a non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to execute a software upgrade method, the method comprising: determining initial idle time prediction information of the air conditioner based on air conditioner operating history data and environmental parameter data; adjusting the initial idle time prediction information based on air conditioner operating control instructions and / or the environmental parameter data; determining a target upgrade time period based on the adjusted idle time prediction information; and performing an upgrade operation on the air conditioner during the target upgrade time period.

[0168] In some embodiments of this disclosure, a computer program product is also provided, including a computer program / instructions. When the computer program / instructions are executed by a processor, they implement a software upgrade method. The method includes: determining initial idle time prediction information of the air conditioner based on historical air conditioner operation data and environmental parameter data; adjusting the initial idle time prediction information based on air conditioner operation control instructions and / or the environmental parameter data; determining a target upgrade time period based on the adjusted idle time prediction information; and performing an upgrade operation on the air conditioner during the target upgrade time period.

[0169] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0170] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A software upgrade method, characterized in that, The software upgrade method includes: Based on historical air conditioner operation data and environmental parameter data, the initial idle time prediction information of the air conditioner is determined; Based on the air conditioning operation control command and / or the environmental parameter data, adjust the initial idle time prediction information to obtain the adjusted idle time prediction information; Based on the adjusted idle time forecast information, the target upgrade time period is determined, including: Get the estimated upgrade time for the upgrade operation; The target upgrade time period is determined based on the estimated upgrade duration and the idle prediction score corresponding to each time period; The air conditioner upgrade operation is performed during the target upgrade time period.

2. The software upgrade method according to claim 1, characterized in that, The step of adjusting the initial idle time prediction information based on the air conditioning operation control command and / or the environmental parameter data includes: A user behavior score is obtained based on the degree of consistency between the air conditioner operation control command and the initial idle time prediction information; The user's intent is evaluated based on the environmental parameter data to obtain a user intent score; Based on the user behavior score and user intent score, determine the predicted update score; The initial idle time prediction information is adjusted based on the predicted updated score.

3. The software upgrade method according to claim 2, characterized in that, The process of obtaining a user behavior score based on the degree of consistency between the air conditioner operation control command and the initial idle time prediction information includes: Determine whether the air conditioner operation control command matches the idle prediction score for the corresponding time period in the initial idle time prediction information; In response to a discrepancy between the air conditioning operation control command and the idle time prediction score for the corresponding time period in the initial idle time prediction information, the user behavior score is determined based on the difference between the air conditioning operation control command and the initial idle time prediction information. The air conditioning operation control commands include at least one of the following: start command, stop command, timer command, working mode setting command, and parameter adjustment command. The working mode setting command includes at least one of the following: heating command, cooling command, defrosting command, and air supply command.

4. The software upgrade method according to claim 2, characterized in that, The process of evaluating user intent based on the environmental parameter data to obtain a user intent score includes: In response to the environmental parameter data changing beyond a threshold, the user's intent is evaluated based on the environmental parameter data to obtain a user intent score. The environmental parameter data includes at least one of temperature data, humidity data, and air quality data.

5. The software upgrade method according to claim 1, characterized in that, The software upgrade method also includes: Determine the preset periodic trigger time; The user behavior trigger time is determined based on the air conditioning operation control command; Based on the periodic trigger time and / or user behavior trigger time, adjustments are made to the initial idle time prediction information.

6. The software upgrade method according to claim 1, characterized in that, The software upgrade method also includes: In response to receiving an interrupt upgrade operation command sent by the user and / or an interrupt upgrade operation command triggered locally by the air conditioner during the execution of the upgrade operation, the execution process of the upgrade operation is interrupted. The interrupt upgrade operation command sent by the user includes at least one of a start command, a working mode setting command, and a parameter adjustment command, and the interrupt upgrade operation command triggered locally by the air conditioner includes at least one of a hardware interrupt command, a software interrupt command, and a self-test interrupt command.

7. The software upgrade method according to claim 1, characterized in that, The determination of the target upgrade time period based on the adjusted idle time prediction information includes: Based on the adjusted idle time forecast information, several candidate upgrade time periods were identified; Based on the user's selected action, the target upgrade time period is determined from the plurality of candidate upgrade time periods.

8. The software upgrade method according to claim 1, characterized in that, The initial idle time prediction information includes idle prediction scores corresponding to multiple time periods.

9. An air conditioner, characterized in that, It is capable of performing the software upgrade method according to any one of claims 1-8.

10. An electronic device, characterized in that... include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the software upgrade method according to any one of claims 1-8.

11. A non-transitory computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to perform the software upgrade method of any one of claims 1-8.

12. A computer program product, characterized in that... It includes a computer program that, when executed by a processor, implements the software upgrade method as described in any one of claims 1-8.

Images