Smart home device control method and apparatus, electronic device, and storage medium

Abstract

The application discloses a control method and device of a smart home device, electronic equipment and a storage medium, and belongs to the technical field of device control. The method comprises the following steps: acquiring multi-source signal data collected for an environment in which a first smart home device is located and a first context mode currently applied by the first smart home device; determining a second context mode corresponding to the current environment of the smart home device according to the multi-source signal data; generating a context mode change event when the first context mode is different from the second context mode; and performing safety parameter configuration control on a second smart home device based on the context mode change event, wherein the second smart home device comprises the first smart home device and / or an online smart home device associated with the first smart home device. The safety parameters are dynamically adjusted, and the risk of privacy leakage is avoided. Meanwhile, cross-device parameter synchronization can be realized, cross-device privacy configuration is ensured, and the safety of user privacy is comprehensively protected.

Description

Technical Field

[0001] This application belongs to the field of equipment control technology, and specifically relates to a control method, device, electronic equipment and storage medium for smart home devices. Background Technology

[0002] Smart home systems typically employ static privacy policy configurations, meaning users manually set data collection permissions and upload policies for each device. Once configured, these policies do not automatically adjust to changes in the home environment. For example, a user might allow cameras to collect data normally when at home, but still upload video data using the same policy when visitors arrive, posing a privacy risk.

[0003] In addition, existing privacy protection solutions are all single-device, single-data type solutions (such as video masking or data encryption only), lacking a unified mechanism for distributing privacy policies across devices, and thus failing to achieve synchronized switching of privacy protection levels across all smart devices in the home. Summary of the Invention

[0004] The purpose of this application is to provide a control method, device, electronic device, and storage medium for smart home devices, which can solve the privacy leakage problem caused by static privacy policy configuration and the problem of cross-device privacy policy synchronization.

[0005] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application provide a method for controlling a smart home device, the method comprising: Acquire multi-source signal data collected for the environment in which the first smart home device is located and the first context mode currently being used by the first smart home device; The second scenario mode corresponding to the current environment of the smart home device is determined based on the multi-source signal data; When the first scenario mode is different from the second scenario mode, a scenario mode change event is generated; Based on the scenario mode change event, the security parameter configuration control of the second smart home device is performed. The second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device.

[0006] Optionally, determining the second context mode corresponding to the current environment of the smart home device based on the multi-source signal data includes: The confidence levels of multiple preset scenarios are determined based on the multi-source signal data; Based on the confidence level, a second scenario mode corresponding to the current environment of the smart home device is determined from the plurality of preset scenarios.

[0007] Optionally, determining the second scenario mode corresponding to the current environment of the smart home device from the plurality of preset scenarios based on the confidence level includes: Candidate scenario patterns are determined from the plurality of preset scenarios based on the confidence level; Determine whether the confidence level of the candidate scenario pattern is greater than or equal to a preset confidence threshold; When the confidence level of the candidate scenario pattern is determined to be greater than or equal to a preset confidence threshold, the candidate scenario pattern is determined as the second scenario pattern corresponding to the current environment of the smart home device.

[0008] Optionally, determining the confidence levels of multiple preset scenarios based on the multi-source signal data includes: Obtain the weight values ​​of the multi-source signal data under different preset scenarios; The matching degree of the multi-source signal data under different preset scenarios is calculated using a preset feature matching function; For any preset scenario, the matching degree is weighted and summed using the weight values ​​to obtain the confidence level corresponding to the preset scenario.

[0009] Optionally, before determining the confidence levels of multiple preset scenarios based on the multi-source signal data, the method further includes: Determine the data type for each type of multi-source signal data; Determine the preprocessing method based on the data type; The multi-source signal data is preprocessed according to the preprocessing method described above.

[0010] Optionally, it includes: Identify the second smart home device corresponding to the first smart home device from the online devices; Based on the scenario mode change event, the security parameter configuration policy corresponding to the second scenario mode is determined from the preset privacy policy table; The security parameter configuration control of the second smart home device is performed in accordance with the security parameter configuration strategy.

[0011] Optionally, it also includes: When the confidence level of the candidate scenario mode is determined to be less than a preset confidence threshold, the second smart home device is controlled to maintain the first scenario mode.

[0012] Secondly, embodiments of this application provide a control device for a smart home device, the device comprising: The data acquisition module is used to acquire multi-source signal data collected for the environment in which the first smart home device is located and the first scenario mode currently applied by the first smart home device; The second scenario mode determination module is used to determine the second scenario mode corresponding to the current environment of the smart home device based on the multi-source signal data. The context mode change event determination module is used to generate a context mode change event when the first context mode is different from the second context mode; The device control module is used to control the security parameter configuration of the second smart home device based on the scenario mode change event. The second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device.

[0013] Thirdly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0014] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0015] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0016] In this embodiment, multi-source signal data collected for the environment of a first smart home device and a first contextual mode currently applied by the first smart home device are acquired. A second contextual mode corresponding to the current environment of the smart home device is determined based on the multi-source signal data. When the first contextual mode and the second contextual mode are different, a contextual mode change event is generated. Based on the contextual mode change event, security parameter configuration control is performed on a second smart home device, which includes the first smart home device and / or online smart home devices associated with the first smart home device. Through this embodiment, the current contextual mode can be determined based on multi-source signal data, and changes can be performed when the current contextual mode does not match the smart home device, achieving dynamic adjustment of security parameters and avoiding privacy leakage risks. Simultaneously, cross-device parameter synchronization can be achieved, ensuring cross-device privacy configuration and comprehensively protecting user privacy and security. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a control method for a smart home device according to an embodiment of this application; Figure 2This is a flowchart illustrating another method for controlling a smart home device according to an embodiment of this application; Figure 3 This is a schematic diagram of a system architecture in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a control device for a smart home device according to an embodiment of this application; Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] Current smart home systems typically employ static privacy policy configurations, meaning users manually set data collection permissions and upload policies for each device. Once configured, these policies do not automatically adjust to changes in the home environment. For example, a user might allow cameras to collect data normally when at home, but still upload video data using the same policy when visitors arrive, posing a privacy risk.

[0020] To avoid privacy leaks, several methods have been disclosed in existing technologies: For example, a method for handling privacy in intelligent surveillance videos discloses the following steps: acquiring the original video stream, performing real-time semantic recognition on the original video stream, and obtaining the semantic recognition result; the semantic recognition result includes object regions of at least one privacy-related category; determining the processing decision for the object region based on a preset set of rules and the semantic recognition result; generating differential masking metadata corresponding to the original video stream according to the processing decision; and encrypting and storing the original video stream and the differential masking metadata separately and in association.

[0021] Another data processing method discloses a set of user data; noise data is added to the user data to obtain perturbed user data; the perturbed user data is encrypted according to a preset homomorphic encryption algorithm to obtain ciphertext user data; wherein the ciphertext user data supports homomorphic operations; the ciphertext user data is sent to a server; so that the server, upon receiving the ciphertext user data, directly processes the ciphertext user data to obtain a processing result. This achieves efficient processing of user data while improving user data security and reducing the risk of user privacy leakage.

[0022] However, current smart home privacy policies are statically configured and cannot automatically adjust the data collection granularity and upload strategy of each device according to changes in the home environment (such as when a visitor arrives, the user is sleeping, or the user is away). This results in the collection and upload of privacy-sensitive data with high privileges even in visitor or sleep scenarios.

[0023] Meanwhile, existing privacy protection solutions are all single-device, single-data type solutions (such as video masking or data encryption only), lacking a unified mechanism for distributing privacy policies across devices, and thus failing to achieve synchronized switching of privacy protection levels across all smart devices in the home.

[0024] In this embodiment, multi-source signal data collected for the environment of the first smart home device and the first scenario mode currently applied by the first smart home device are acquired; a second scenario mode corresponding to the current environment of the smart home device is determined based on the multi-source signal data; when the first scenario mode and the second scenario mode are different, a scenario mode change event is generated; and security parameter configuration control is performed on the second smart home device based on the scenario mode change event, wherein the second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device.

[0025] In this application embodiment, on the one hand, the current applicable scenario mode can be determined by collecting multi-source information data. When the scenario mode is different from the actual scenario mode, the scenario mode can be changed in a timely manner. On the other hand, when the scenario mode is changed, cross-device synchronous control can be realized, so that multiple associated online smart home devices can be configured with security parameters, improve device control efficiency, and achieve comprehensive privacy and security protection.

[0026] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0027] The control method for smart home devices provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0028] like Figure 1 The diagram shown is a flowchart illustrating a control method for a smart home device according to an embodiment of this application, which may specifically include the following steps: Step S101: Acquire multi-source signal data collected for the environment where the first smart home device is located and the first scenario mode currently applied by the first smart home device; The current leading smart home devices can be set with different scenario modes to protect user privacy and security in different scenarios.

[0029] In practical applications, a data acquisition device can be set up in the environment where the first smart home device is located. This data acquisition device can collect multi-source signal data of the environment where the first smart home device is located. The multi-source signal data can be used to distinguish data from different scenarios, such as the open or closed status of doors and windows, infrared sensor signals, Bluetooth pairing signals, time data, etc.

[0030] The first scenario mode is the scenario mode that the first smart home device is currently using.

[0031] In one embodiment of this application, before determining the second scenario mode corresponding to the current environment of the smart home device based on the multi-source signal data, the data type of each type of multi-source signal data can be determined; a preprocessing method can be determined based on the data type; and then the multi-source signal data can be preprocessed according to the preprocessing method.

[0032] For example, the system performs normalization preprocessing on the raw signals collected from each sensor: (1) The gate magnetic state is discretized into a binary signal s1∈{0,1} (0 represents closure, 1 represents triggering); (2) After the Bluetooth scanning results are matched with the device pairing library, the online ratio of paired devices s2∈[0,1] and the detection flag of unpaired unfamiliar devices s3∈{0,1} are output. (3) The human infrared sensor signal is smoothed by a 10-second sliding window and outputs the motion activity s4∈[0,1] (0 represents complete stillness, 1 represents continuous motion). (4) The current time is mapped to the time feature vector s5=(t_deep_night, t_workday), where t_deep_night∈{0,1} indicates whether it is in the late night period from 22:00 to 6:00, and t_workday∈{0,1} indicates whether it is in the workday.

[0033] Step S102: Determine the second scenario mode corresponding to the current environment of the first smart home device based on the multi-source signal data; After acquiring multi-source signal data, the context mode of the current environment of the first smart home device can be determined based on the correlation between the multi-source signal data and different context modes.

[0034] Step S103: When the first scenario mode is different from the second scenario mode, a scenario mode change event is generated; The first context mode is the currently applied context mode, and the second context mode is the most suitable context mode. If the two are different, it is determined that the currently applied context mode is not suitable for the current environment, and a context mode change event can be generated. This context mode change event is used to trigger the context mode switch.

[0035] Step S104: Based on the scenario mode change event, perform security parameter configuration control on the second smart home device, the second smart home device including the first smart home device and / or online smart home devices associated with the first smart home device.

[0036] After generating a context mode change event, the security parameters of the second smart home device can be configured and controlled according to the event to ensure that the second smart home device is adapted to the current scenario and effectively avoid privacy leakage.

[0037] In this embodiment, the control of the first smart home device can be extended to the control of other online smart home devices, enabling cross-device privacy and security synchronous control.

[0038] In one embodiment of this application, the step of controlling the security parameter configuration of the second smart home device based on the context mode change event includes: determining the second smart home device corresponding to the first smart home device from devices that are online; determining the security parameter configuration policy corresponding to the second context mode from a preset privacy policy table based on the context mode change event; and controlling the security parameter configuration of the second smart home device according to the security parameter configuration policy.

[0039] Once the context-aware engine infers a new context mode through analysis, it can immediately send a context mode change event to the strategy linkage execution layer. A new context mode refers to a situation where "the current family context has switched from the original context mode to another predefined context mode" (i.e., the current judgment context is inconsistent with the context determined in the previous judgment cycle). This system predefines four core family context modes (Normal Home, Visitor, Sleep, and Out). The role of the context-aware engine is to switch between these four predefined modes in real time, rather than dynamically creating new context modes. The judgment cycle is set to execute once every 30 seconds by default to ensure timely response to changes in the family environment; at the same time, the system retains the ability to expand to new context modes through firmware upgrades.

[0040] As the system's policy scheduling center, the Agent runtime receives change events and queries the preset privacy policy level table for the specific privacy policy configuration corresponding to the current scenario mode. Then, through a unified device control protocol, it sends policy switching commands in parallel to all online smart devices in the home. This parallel sending method avoids policy switching delays caused by waiting for each device individually, improving control efficiency. Upon receiving the command, each smart device immediately executes the corresponding privacy protection operation, including data collection degradation and closing sensitive data transmission channels. After execution, it sends an execution confirmation message back to the Agent runtime. This message contains key information such as the device's unique identifier, policy execution status, and execution timestamp. If a device does not send an execution confirmation message within 3 seconds, the Agent runtime marks the device as having a policy not executed and displays a notification on the user's mobile terminal, facilitating timely troubleshooting.

[0041] The preset privacy policy level table defines four privacy protection levels (L0~L3), and the mapping relationship between each scenario mode and the privacy level is shown in Table 1:

[0042] Table 2 shows the specific operation mapping table for each device type under the four privacy levels:

[0043] Note: Safety sensors (smoke, gas, etc.) maintain real-time reporting at all privacy levels and are not affected by privacy policy downgrades, ensuring the safety of family life and property.

[0044] Each scenario mode corresponds to a different privacy protection strategy to ensure that privacy protection and usage needs are precisely matched: In visitor mode, the camera only outputs human silhouette skeleton data and does not transmit raw video frames. The voice device only performs local wake word detection, closes keyword extraction and reporting channels, the temperature and humidity sensor reduces the sampling frequency to once every 5 minutes, and the door lock device prohibits remote unlocking commands; In sleep mode, the level of privacy protection is further enhanced. The camera closes the cloud upload channel and only retains the local recording function. The voice device closes the audio acquisition function and only retains the emergency wake-up detection function. All kinds of sensors report data at the lowest frequency; In away mode, the camera enters security mode and only supports motion detection alarm information upload. The voice device is completely turned off to avoid any audio data being collected. The sensors only report data when abnormal values ​​are detected. The door lock device enables the anti-tamper alarm function, comprehensively protecting family privacy and property security.

[0045] The audit log module records every privacy policy change event in real time. The log includes the policy change timestamp, the context before and after the change, a list of affected smart devices, and the execution confirmation status of each device. The logs are encrypted using the AES-256-GCM encryption algorithm, archived on a rolling basis by calendar month, and retained for at least three years. Users can access historical change records at any time via mobile devices, providing traceable evidence for privacy protection compliance reviews.

[0046] The specific scenarios that trigger changes to privacy policies include the following four categories: I. Mode Switching Trigger. When the context-aware engine determines that the home context has switched from one predefined mode to another (e.g., home → visitor, sleep → away), it automatically triggers a change in the privacy policy level. This is the most common trigger scenario, driven by the periodic judgment results of the weighted fusion algorithm. The judgment period is 30 seconds, and if a change in context is detected each time, the policy change is triggered immediately.

[0047] II. User Manual Intervention Trigger. When a user actively selects a specific context mode via a mobile app or voice command, the system prioritizes the user-specified mode and immediately triggers the corresponding privacy policy change. After the user manually selects the mode, the context-aware engine pauses its automatic judgment function until the user cancels the manual mode or the duration of the manual mode exceeds a preset time limit (default 2 hours), at which point the system automatically resumes the automatic judgment mode.

[0048] 3. Triggering Online / Offline Status. When a new smart device is added to the home network or an existing device goes offline, the Agent runtime triggers a policy synchronization operation: when a new device comes online, it immediately obtains the currently effective privacy policy level and applies it to the device; when a device is offline for more than the heartbeat timeout threshold (default 30 seconds), the Agent runtime records the device offline event in the audit log and adjusts the policy execution status of the remaining online devices to ensure the consistency of overall privacy protection.

[0049] IV. Time-Based Policy Triggering. The system supports users to preset time-based privacy policy rules, such as "automatically enter sleep mode at 22:00 every day" and "default to out mode from 9:00 to 18:00 on weekdays". When the preset time arrives, if the current context-aware engine's judgment result is inconsistent with the timed policy, the system will prioritize the timed policy to change the privacy policy. The priority of the timed policy is between user manual selection and automatic context determination.

[0050] The audit logs record the following fields for all four trigger scenarios: trigger type (scenario switching / user manual / device online / offline / timed policy), trigger timestamp, scenario mode and privacy level before change, scenario mode and privacy level after change, specific information of the trigger source (such as confidence score, user operation device ID, device MAC address, timed policy ID), and a summary of policy distribution results.

[0051] In one embodiment of this application, when the triggering conditions of multiple scenario modes are met simultaneously (i.e., there are multiple second scenario modes that meet the conditions), the system adopts the principle of prioritizing the strictest privacy policy for conflict arbitration. The scenario priority is from high to low as follows: scenario mode manually selected by the user > out mode > sleep mode > visitor mode > normal home mode. Finally, the strictest privacy restriction conditions in each scenario are executed to ensure the comprehensiveness of privacy protection.

[0052] Example 1: Visitor arrives during weekday off hours. At 10:00 AM on Wednesday, the user has already left home for work (off-duty conditions are met). At this time, the door magnetic sensor detects that the door is open and scans for an unfamiliar Bluetooth device (visitor mode conditions are met).

[0053] Conflict analysis: When the triggering conditions for both Outgoing Mode and Visitor Mode are met simultaneously, the priority order is: Outgoing Mode > Visitor Mode.

[0054] Arbitration Result: Determined to be in Away Mode, the system adopts L3 (High Degradation) privacy level. At this level, the camera only outputs motion detection alarms, and the voice device is completely turned off. Although a visitor entered, considering that the user is not at home, the strictest privacy protection strategy is more in line with security needs—ensuring that home devices are not used for privacy theft during this period. The user's mobile phone will receive a motion detection alarm notification (including a timestamp and trigger sensor ID), and the user can decide whether to manually switch to Guest Mode to authorize temporary access based on the alarm.

[0055] Example 2: User manually selects guest mode during late-night sleep. At 1:00 AM, the system has automatically entered sleep mode (L2). At this time, the user, waiting for family members to return late, manually selects to enter guest mode through the app.

[0056] Conflict analysis: The triggering conditions for sleep mode (automatic determination) and guest mode (user manual selection) coexist, and the priority order is: user manual selection > sleep mode.

[0057] Arbitration Result: The user-selected option had the highest priority, and the system switched to visitor mode (L1). However, the arbitration engine refined the process—adjusting only the door lock and camera policies to visitor level (allowing entrant identification), while the voice device and other sensors remained under the higher privacy restrictions of sleep mode (L2), as other family members were still asleep. User Perception: The camera resumed human detection to identify late-returning family members, but the voice assistant did not resume its listening function, balancing security and privacy.

[0058] Example 3: Comprehensive Conflict Arbitration When Multiple Conditions Are Met Simultaneously. At 3:00 PM on a weekday afternoon, the nanny arrives as agreed (door sensor triggered + detection of unfamiliar Bluetooth devices → visitor conditions met). However, the user manually sets the system to "away mode" via the app (because they are on vacation and do not want anyone to enter). Conflict Analysis: There are three scenario judgment signals—automatically determined visitor mode, automatically determined away mode (weekday + Bluetooth offline), and user-manually selected away mode. Ultimately, arbitration is based on the "strictest policy for each device": Table 3 Equipment Arbitration Results

[0059] The so-called "strictest privacy restrictions" refer to, for each type of smart device, among all conflicting scenario modes, selecting the set of policy parameters that imposes the most stringent data collection permission requirements on that device (i.e., the lowest data collection granularity, the most restricted transmission channels, and the shortest data retention time). The arbitration engine adopts a fine-grained arbitration approach on a device-by-device and dimension-by-dimensional basis, rather than simply selecting the entire scenario mode, to ensure that privacy protection vulnerabilities do not arise due to scenario conflicts.

[0060] This application embodiment can achieve accurate inference of home scenarios through multi-source sensor signal fusion, realize unified linkage across devices by relying on the Agent scheduling center, and combine device execution confirmation and encrypted audit log mechanism to actively control privacy protection from the data collection source. It belongs to the ex-ante defense mode, which complements the ex-ante privacy protection technology of existing patents. It can be widely used in various smart home systems and has high practicality and promotion value.

[0061] In this embodiment, multi-source signal data collected for the environment of a first smart home device and a first contextual mode currently applied by the first smart home device are acquired. A second contextual mode corresponding to the current environment of the smart home device is determined based on the multi-source signal data. When the first contextual mode and the second contextual mode are different, a contextual mode change event is generated. Based on the contextual mode change event, security parameter configuration control is performed on a second smart home device, which includes the first smart home device and / or online smart home devices associated with the first smart home device. Through this embodiment, the current contextual mode can be determined based on multi-source signal data, and changes can be performed when the current contextual mode does not match the smart home device, achieving dynamic adjustment of security parameters and avoiding privacy leakage risks. Simultaneously, cross-device privacy and security parameter synchronous configuration can be achieved, realizing comprehensive privacy and security protection.

[0062] like Figure 2 The diagram shown is a flowchart illustrating a control method for a smart home device according to an embodiment of this application, which may specifically include the following steps: Step S201: Acquire multi-source signal data collected for the environment in which the first smart home device is located and the first scenario mode currently applied by the first smart home device; Step S202: Determine the confidence levels of multiple preset scenarios based on the multi-source signal data; The confidence level is used to represent the matching degree between multi-source signal data and the preset scenario.

[0063] In one embodiment of this application, determining the confidence level of multiple preset scenarios based on the multi-source signal data includes: obtaining the weight values ​​of the multi-source signal data under different preset scenarios; calculating the matching degree of the multi-source signal data under different preset scenarios using a preset feature matching function; and for any preset scenario, performing a weighted summation calculation on the matching degree using the weight values ​​to obtain the confidence level corresponding to the preset scenario.

[0064] In practical applications, a set of weight values ​​can be predefined for each situational pattern. Define a set of situational patterns C = {home, visitor, sleep, out}, and for each situation c ∈ C, calculate its confidence score: Conf(c) = Σ i w_c,i × f_c,i(s_i) Where w_c,i is the weight of signal i under scenario c (preset by the system or learned through historical data), and f_c,i is the feature matching function of signal i under scenario c, which outputs the degree of matching between the signal and the expected scenario.

[0065] The weight allocation for each scenario is shown in Table 4 below:

[0066] Step S203: Based on the confidence level, determine the second scenario mode corresponding to the current environment of the smart home device from the plurality of preset scenarios.

[0067] In one embodiment of this application, determining the second scenario mode corresponding to the current environment of the smart home device from the plurality of preset scenarios based on the confidence level includes: determining a candidate scenario mode from the plurality of preset scenarios based on the confidence level; determining whether the confidence level of the candidate scenario mode is greater than or equal to a preset confidence threshold; and determining the candidate scenario mode as the second scenario mode corresponding to the current environment of the smart home device when the confidence level of the candidate scenario mode is greater than or equal to the preset confidence threshold.

[0068] In another embodiment of this application, when the confidence level of the candidate scenario mode is determined to be less than a preset confidence threshold, the second smart home device is controlled to maintain the first scenario mode.

[0069] After calculating the confidence scores for all scenarios, the scenario with the highest confidence score can be selected as the candidate scenario c*. If the confidence score Conf(c*) of c* is greater than or equal to the preset confidence threshold, then the current family scenario is determined to switch to c*; otherwise, the current scenario remains unchanged to prevent frequent switching caused by signal jitter.

[0070] In addition, the system sets enhanced judgment conditions for the outing mode: even if the outing mode has the highest confidence level, it still needs to meet the triple protection mechanism (multi-round scan confirmation, RSSI filtering, and comprehensive confidence level ≥ 0.7) before the outing mode judgment is triggered.

[0071] Step S204: When the first scenario mode is different from the second scenario mode, a scenario mode change event is generated; Step S205: Based on the scenario mode change event, perform security parameter configuration control on the second smart home device, the second smart home device including the first smart home device and / or online smart home devices associated with the first smart home device.

[0072] In this embodiment, multi-source signal data collected for the environment of a first smart home device and a first contextual mode currently applied by the first smart home device are acquired. Confidence levels for multiple preset contexts are determined based on the multi-source signal data. A second contextual mode corresponding to the current environment of the smart home device is determined from the multiple preset contexts based on the confidence levels. When the first contextual mode and the second contextual mode are different, a contextual mode change event is generated. Based on the contextual mode change event, security parameter configuration control is performed on the second smart home device, which includes the first smart home device and / or online smart home devices associated with the first smart home device. Through this embodiment, the current contextual mode can be determined based on multi-source signal data, and changes can be performed when the current contextual mode does not match the smart home device, thereby dynamically adjusting security parameters and avoiding privacy leakage risks.

[0073] like Figure 3 The diagram shown is a flowchart of one possible application, which may include the following processes: The context-aware engine collects multi-source signal data; it analyzes the multi-source signal data using a weighted fusion algorithm to obtain the confidence level corresponding to each context, performs context inventory and confidence level verification. If the confidence level is greater than or equal to the preset confidence threshold (0.6), the mode is determined to be home / visitor / sleep / outing mode, etc.; if the confidence level is less than 0.6, the original context is maintained.

[0074] When multiple scenarios are triggered, conflict arbitration is performed. In conflict arbitration, strict strategy is prioritized and manual is the highest priority, followed by the priority of different scenarios: manual > out > sleep > visitors > home.

[0075] The intelligent agent issues control commands corresponding to parallel scenario changes. The device executes the strategy corresponding to the scenario. If the execution is confirmed, the log is encrypted and archived. If not confirmed, the terminal reminds and records the log, and continues to execute the cyclic sensing control.

[0076] It should be noted that the control method for smart home devices provided in this application embodiment can be executed by a control device for the smart home device, or a control module within the control device for executing the control method for loading the smart home device. This application embodiment uses the execution of the control method for loading the smart home device by a control device for the smart home device as an example to illustrate the control method for smart home devices provided in this application embodiment.

[0077] like Figure 4 The diagram shown is a flowchart illustrating a control device for a smart home device according to an embodiment of this application. Specifically, it may include the following structure: Data acquisition module 401 is used to acquire multi-source signal data collected for the environment in which the first smart home device is located and the first scenario mode currently applied by the first smart home device; The second scenario mode determination module 402 is used to determine the second scenario mode corresponding to the current environment of the smart home device based on the multi-source signal data. The context mode change event determination module 403 is used to generate a context mode change event when the first context mode is different from the second context mode; The device control module 404 is used to control the security parameter configuration of the second smart home device based on the scenario mode change event. The second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device.

[0078] In one embodiment of this application, the second scenario mode determination module 402 may include: The confidence level determination submodule is used to determine the confidence level of multiple preset scenarios based on the multi-source signal data; The second scenario mode determination submodule is used to determine the second scenario mode corresponding to the current environment of the smart home device from the plurality of preset scenarios based on the confidence level.

[0079] In one embodiment of this application, the second scenario mode determination submodule may include: A candidate scenario pattern determination unit is used to determine candidate scenario patterns from the plurality of preset scenarios based on the confidence level; A confidence judgment unit is used to determine whether the confidence of the candidate scenario pattern is greater than or equal to a preset confidence threshold. The second scenario mode determination unit is used to determine the candidate scenario mode as the second scenario mode corresponding to the current environment of the smart home device when the confidence level of the candidate scenario mode is greater than or equal to a preset confidence threshold.

[0080] In one embodiment of this application, the confidence level determination submodule may include: The weight value acquisition unit is used to acquire the weight values ​​of the multi-source signal data under different preset scenarios. The matching degree determination unit is used to calculate the matching degree of the multi-source signal data under different preset scenarios using a preset feature matching function; The confidence level determination unit is used to calculate the confidence level corresponding to any preset scenario by weighting and summing the matching degree using the weight value.

[0081] In one embodiment of this application, the apparatus further includes: The data type determination module is used to determine the data type of each type of multi-source signal data; A preprocessing method determination module is used to determine the preprocessing method based on the data type. A preprocessing mode is used to preprocess the multi-source signal data according to the preprocessing method.

[0082] In one embodiment of this application, the device control module 404 may include: The second smart home device determination submodule determines the second smart home device corresponding to the first smart home device from the online devices. The security parameter configuration policy determination submodule is used to determine the security parameter configuration policy corresponding to the second scenario mode from a preset privacy policy table based on the scenario mode change event. The device control module is used to control the security parameters of the second smart home device in accordance with the security parameter configuration strategy.

[0083] In one embodiment of this application, the second scenario mode determination submodule further includes: The scenario mode maintenance unit is used to control the second smart home device to maintain the first scenario mode when the confidence level of the candidate scenario mode is determined to be less than a preset confidence threshold.

[0084] In this embodiment, multi-source signal data collected for the environment of a first smart home device and a first contextual mode currently applied by the first smart home device are acquired. A second contextual mode corresponding to the current environment of the smart home device is determined based on the multi-source signal data. When the first contextual mode and the second contextual mode are different, a contextual mode change event is generated. Based on the contextual mode change event, security parameter configuration control is performed on a second smart home device, which includes the first smart home device and / or online smart home devices associated with the first smart home device. Through this embodiment, the current contextual mode can be determined based on multi-source signal data, and changes can be performed when the current contextual mode does not match the smart home device, achieving dynamic adjustment of security parameters and avoiding privacy leakage risks. Simultaneously, cross-device parameter synchronization can also be achieved, ensuring cross-device privacy configuration and comprehensively protecting user privacy and security.

[0085] The control device for smart home devices in this application embodiment can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, mobile electronic devices can be mobile phones, tablets, laptops, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs), etc., while non-mobile electronic devices can be servers, network-attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not impose specific limitations.

[0086] The control device for the smart home device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0087] The control device for smart home devices provided in this application embodiment can achieve… Figures 1 to 2 The various processes implemented by the control device of the smart home device in the method embodiment will not be described again here to avoid repetition.

[0088] Optionally, this application embodiment also provides an electronic device, including a processor 1010, a memory 1009, and a program or instructions stored in the memory 1009 and executable on the processor 1010. When the program or instructions are executed by the processor 1010, they implement the various processes of the above-described smart home device control method embodiment and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0089] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0090] Figure 5 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application. The electronic device 1000 includes, but is not limited to, the following components: radio frequency unit 1001, network module 1002, audio output unit 1003, input unit 1004, sensor 1005, display unit 1006, user input unit 1007, interface unit 1008, memory 1009, and processor 1010.

[0091] The memory 1009 includes applications and an operating system; the user input unit 1007 may include a touch panel 10071 and other input devices 10072; the input unit 1004 may include an image processor 10041 and a microphone 10042; and the display unit 1006 may include a display panel 10061.

[0092] Those skilled in the art will understand that the electronic device 1000 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1010 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 5 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here. This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described smart home device control method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0093] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0094] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described smart home device control method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0095] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0096] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0097] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0098] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A control method for a smart home device, characterized in that, The method includes: Acquire multi-source signal data collected for the environment in which the first smart home device is located and the first context mode currently being used by the first smart home device; The second scenario mode corresponding to the current environment of the first smart home device is determined based on the multi-source signal data; When the first scenario mode and the second scenario mode are different, a scenario mode change event is generated; Based on the scenario mode change event, the security parameter configuration control of the second smart home device is performed, wherein the second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device; The step of configuring and controlling the security parameters of the second smart home device based on the context mode change event includes: Identify the second smart home device corresponding to the first smart home device from the online devices; Based on the scenario mode change event, the security parameter configuration policy corresponding to the second scenario mode is determined from the preset privacy policy table; The security parameter configuration control of the second smart home device is performed in accordance with the security parameter configuration strategy.

2. The method according to claim 1, characterized in that, Determining the second context mode corresponding to the current environment of the smart home device based on the multi-source signal data includes: The confidence levels of multiple preset scenarios are determined based on the multi-source signal data; Based on the confidence level, a second scenario mode corresponding to the current environment of the smart home device is determined from the plurality of preset scenarios.

3. The method according to claim 2, characterized in that, The step of determining the second scenario mode corresponding to the current environment of the smart home device from the plurality of preset scenarios based on the confidence level includes: Candidate scenario patterns are determined from the plurality of preset scenarios based on the confidence level; Determine whether the confidence level of the candidate scenario pattern is greater than or equal to a preset confidence threshold; When the confidence level of the candidate scenario pattern is determined to be greater than or equal to a preset confidence threshold, the candidate scenario pattern is determined as the second scenario pattern corresponding to the current environment of the smart home device.

4. The method according to claim 2, characterized in that, The step of determining the confidence levels of multiple preset scenarios based on the multi-source signal data includes: Obtain the weight values ​​of the multi-source signal data under different preset scenarios; The matching degree of the multi-source signal data under different preset scenarios is calculated using a preset feature matching function; For any preset scenario, the matching degree is weighted and summed using the weight values ​​to obtain the confidence level corresponding to the preset scenario.

5. The method according to claim 1, characterized in that, Before determining the second context mode corresponding to the current environment of the smart home device based on the multi-source signal data, the method further includes: Determine the data type for each type of multi-source signal data; Determine the preprocessing method based on the data type; The multi-source signal data is preprocessed according to the preprocessing method described above.

6. The method according to claim 1, characterized in that, Also includes: When the confidence level of the candidate scenario mode is determined to be less than a preset confidence threshold, the second smart home device is controlled to maintain the first scenario mode.

7. A control device for a smart home device, characterized in that, The device includes: The data acquisition module is used to acquire multi-source signal data collected for the environment in which the first smart home device is located and the first scenario mode currently applied by the first smart home device; The second scenario mode determination module is used to determine the second scenario mode corresponding to the current environment of the smart home device based on the multi-source signal data. The context mode change event determination module is used to generate a context mode change event when the first context mode is different from the second context mode; The device control module is used to control the security parameter configuration of the second smart home device based on the scenario mode change event, wherein the second smart home device includes the first smart home device and / or online smart home devices associated with the first smart home device; The device control module includes: The second smart home device determination submodule determines the second smart home device corresponding to the first smart home device from the online devices. The security parameter configuration policy determination submodule is used to determine the security parameter configuration policy corresponding to the second scenario mode from a preset privacy policy table based on the scenario mode change event. The device control module is used to control the security parameters of the second smart home device in accordance with the security parameter configuration strategy.

8. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the control method for the smart home device as described in any one of claims 1 to 6.

9. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the control method for the smart home device as described in any one of claims 1 to 6.

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