Rule modification in automation system

Abstract

In one aspect, a computer-implemented method for modifying rules in a control hub is provided, the control hub being connected to one or more devices and configured to provide at least one of audio and visual information, the method including obtaining (210) a base routine rule layer for controlling the devices in a usage scenario, the base routine rule layer being based on historical data associated with a user's routine, obtaining (220) sensor data and / or device data from at least one of the one or more devices, determining (230) whether there is an interference event based on an evaluation of the sensor data and / or device data, the interference event conflicting with the base routine rule layer, generating (240) an additional routine rule layer based on the sensor data and / or device data upon determining there is an interference event, executing the additional routine rule layer, and storing the additional routine rule layer in a rule database of the control hub.

Description

[Technical field]

[0001] The present disclosure relates to a method for modifying rules in a control hub connected to one or more devices, and a control hub having rule modification functionality. [Background technology]

[0002] Home automation systems and assistants, such as voice-assisted (or voice-controlled) control hubs that interact with users through audio / voice input / output, are becoming more popular with the growth of the Internet and cloud computing. These systems can connect to a multitude of devices (e.g., electric toothbrushes) and provide an interface to provide various types of information, including instructions for using the devices. Additionally, users can interact with entertainment devices (e.g., televisions, streaming devices, gaming consoles, etc.) connected to the control hub by using speech such as "turn on the living room TV" or "set the volume of the living room TV to 25". The control hub includes an intelligent decision layer that fuses multiple sensor inputs from multiple appliances, processes the inputs based on predefined rules or thresholds, triggers voice responses in the backend (cloud), and delivers certain events via a user interface on the auxiliary device or appliance. The delivery of such speech may occur alone or in combination with the display of appropriate information related to the event via various cognitive cues.

[0003] For example, the control hub is responsible for authorizing appropriate voice responses when multiple devices are used simultaneously in a bathroom ecosystem. FIG. 1 is a schematic diagram of a hub system including a hub layer and a network layer. The hub layer includes a control hub 110 connected to a speaker device 120 and multiple local connectivity devices 130, 140, and 150. The network layer includes a network 160 to which the hub 110 is connected, which is also connected to a cloud-based service 170. The hub 110 can receive instructions from a voice assistant device (not shown) along with the cloud-based service 170 to change parameters of a device (e.g., an electric shaver). The hub 110 can act on such intent and change the parameters of the device. Summary of the Invention [Problem to be solved by the invention]

[0004] A voice-first user interface is different from an on-screen interaction. On the web or mobile for example there is a single user interface that dynamically displays personal content such as music preferences. In addition to the personal content, a voice interaction can personalize the interaction itself. A voice-first interaction offers the possibility to create an individual user profile. From a user experience point of view, the interaction should be predictable, yet varied and enjoyable. In a multi-device scenario this can be done by adapting existing rules (from past usage) and creating new rules, validating them with real-time sensor or device data.

[0005] There are several shortcomings associated with currently available automation and / or assistance systems that are addressed by the embodiments proposed in this disclosure. [Means for solving the problem]

[0006] According to a first particular aspect, a computer-implemented method for modifying rules in a control hub is provided. The control hub is connected to one or more devices and configured to provide at least one of audio information and visual information. The method includes the steps of: acquiring a basic routine rule layer for controlling one or more devices in a usage scenario, the basic routine rule layer being based on past data related to a user's routine; acquiring at least one of sensor data and device data from at least one or more devices; determining whether there is an interference event based on an evaluation of the at least one of the sensor data and the device data, the interference event conflicting with the basic routine rule layer; generating an additional routine rule layer based on the at least one of the sensor data and the device data upon determining that there is an interference event, the additional routine rule layer being for controlling one or more devices in the usage scenario when the interference event occurs; executing the additional routine rule layer; and storing the additional routine rule layer in a rule database of the control hub.

[0007] In some embodiments, obtaining a base routine rule layer for controlling the one or more devices may include obtaining historical data related to a user's routines on at least one of the one or more devices, and generating a base routine rule layer based on the obtained historical data.

[0008] In some embodiments, the method may further include the steps of determining whether the additionally acquired sensor data and / or device data indicates that an interference event has occurred after generating the additional routine rule layer, and in response to a determination based on the additionally acquired sensor data and / or device data that an interference event has not occurred after generating the additional routine rule layer, selecting a basic routine rule layer from the rules database, or in response to a determination based on the additionally acquired sensor data and / or device data that an interference event has occurred after generating the additional routine rule layer, selecting an additional routine rule layer from the rules database, and instructing the selected basic or additional routine rule layer to be executed to control one or more devices in accordance with the selected basic or additional routine rule layer.

[0009] In some embodiments, after generating the additional routine rule layer, the method may include determining whether the additional routine rule layer still applies based on whether an interference event has occurred within a specified period of time, and deleting the additional routine rule layer from the rules database in response to determining that an interference event has not occurred within the specified period of time.

[0010] In some embodiments, the method further includes obtaining a user interaction to confirm consent to the additional routine rule layer, and the steps of executing the additional routine rule layer and saving the additional routine rule layer may be performed only upon obtaining a user interaction to confirm consent to the additional routine rule layer.

[0011] In some embodiments in which the control hub is connected to multiple devices, the basic routine rule layer determines a first relative priority of use of at least a subset of the multiple devices, and the additional routine rule layer determines a second relative priority of use of at least a subset of the multiple devices to respond to or avoid an interference event, the second relative priority of use being different from the first relative priority of use.

[0012] In some embodiments where the control hub is connected to multiple devices, the basic routine rule layer determines a first device of the multiple devices to use in the usage scenario, and the additional routine rule layer determines a second device of the multiple devices to use in the usage scenario, where the second device is different from the first device, to respond to or avoid an interference event.

[0013] In some embodiments, the basic routine rule layer determines a first operating mode for a device of one or more devices used in the usage scenario, and the additional routine rule layer determines a second operating mode for a device used in the usage scenario to respond to or avoid an interference event, the second operating mode being different from the first operating mode.

[0014] In some embodiments, the sensor data may include at least one of device time data, device motion sensor data, device accelerometer data, device rotation sensor data, device angle sensor data, device battery level data, device pressure sensor data, device stroke length sensor data, device stroke rate sensor data, device stroke density sensor data, device touch sensor data, device interruption sensor data, device distance sensor data, device grip sensor data, device hair density sensor data, device hair length sensor data, device environmental sensor data, device displacement sensor data, device motion sensor data, device skin moisture sensor data, device skin oil sensor data, device skin pH sensor data, device pulse sensor data, device image sensor data, and device accessory sensor data.

[0015] In some embodiments, the device data may include at least one of a battery level status of the device, time remaining for an action corresponding to the device, a cleanliness status of the device, a wear status of the device, usage statistics related to accessories of the device, revolutions per minute (RPM) for the device, a torque level of the device, an operating mode or function of the device, a connectivity status of the device, time spent in a body zone of the device, and operational metrics of the device.

[0016] In some embodiments, the sensor data includes at least one of device skin moisturization sensor data and device skin oil content sensor data, an interference event occurs when a user's skin moisturization level or a user's skin oil content exceeds a predetermined threshold.

[0017] In embodiments in which the sensor data includes battery level data for the device and / or the device data includes a battery level status for the device, an interference event occurs when the battery level of the device is below a predetermined threshold or when the battery level of the device is lower than the battery level of another device connected to the control hub.

[0018] In some embodiments where the device data includes a cleanliness status of the device, an interference event occurs when the cleanliness status of the device is below a predefined threshold.

[0019] In some embodiments, the one or more devices include one or more of an electric toothbrush, an electric shaver, an oral cleaning device, an interdental device, a hair care device, a hair removal device, a skin care device, a body grooming device, an epilation device, an intense pulsed light (IPL) device, and a body trimming device.

[0020] According to a second particular aspect, there is provided a computer program comprising a computer readable medium having computer readable code embodied therein, the computer readable code being configured to, when executed by a suitable computer or processor, cause the computer or processor to perform a method as described herein.

[0021] According to a third particular aspect, a control hub connected to one or more devices is provided, the control hub comprising a processing circuit configured to provide at least one of audio information and visual information, and to perform the steps of: acquiring a basic routine rule layer for controlling one or more devices in a usage scenario, the basic routine rule layer being based on historical data related to a user's routine; acquiring at least one of sensor data and device data from at least one of the one or more devices, determining whether there is an interference event based on an evaluation of the at least one of the sensor data and device data, the interference event conflicting with the basic routine rule layer; generating an additional routine rule layer based on the at least one of the sensor data and device data upon determining there is an interference event, the additional routine rule layer being for controlling one or more devices in the usage scenario when an interference event occurs; executing the additional routine rule layer; and storing the additional routine rule layer in a rule database of the control hub.

[0022] These and other aspects will be apparent from and elucidated with reference to the embodiments described hereinafter.

[0023] The proposed method and control hub of the present disclosure provide many technical advantages.

[0024] For example, the rule modification method and functionality allows combining data streams (real-time, current, and historical) from multiple devices and fusing them to build new rule layers via natural user interactions, thus adapting to new scenarios and new interactions with the user to provide seamless and convenient services, thus enhancing the user friendliness of the Control Hub. Certain embodiments of the present disclosure allow for the assignment (and reassignment) of device usage priorities based on real-time sensor and / or device data, allowing users to complete their normal routines even in the event of an interference event. Additionally, certain embodiments allow for the assignment of unique voice signatures as well as responses via unique voice signatures for each device and / or user profile available in the connected system.

[0025] In some cases, a user of one or more devices may have a routine. This means that the basic routine rule layer is always applied. However, another user of one or more devices may be associated with an interference event, so an additional routine rule layer is generated for this user. The additional routine rule layer may increase personalization of the user. However, the basic routine rule layer may still be used, such as when the interference event does not occur again or is no longer relevant. Thus, the routine rule layer for controlling one or more devices associated with the user may be personalized for the user. A control hub for modifying rules may use computational resources (e.g., storage and / or processing) to generate and / or store the additional routine rule layer. Storing the additional routine rule layer (e.g., in persistent non-volatile storage of the control hub) may reduce the need to repeat the processing effort used to initially create the additional routine rule layer (e.g., if the same interference event occurs again). Personalization of the routine rule layer at the control hub may reduce unnecessary processing and / or storage of the additional routine rule layer in a network that includes multiple control hubs (e.g., rather than deploying a single rule set to all users in the network). In some cases, the need to temporarily store data about rules in volatile storage (e.g., random access memory) in the Control Hub can be reduced. This can free up memory resources for other tasks in the Control Hub. In some cases, it can be computationally simple to implement and use a rule layer structure that includes a base routine rule layer and an additional routine rule layer. Rather than implementing a single large and complex rule set, e.g., to control one or more devices, one of the base and additional routine rule layers can be selected to execute (e.g., to control one or more devices according to the selected routine rule layer).In some cases, separating rules into routine rule layers may facilitate quick access, processing, and implementation of individual routine rule layers (e.g., without executing the entire rule set). In some cases, unused or irrelevant routine rule layers may be deleted to free up memory in the Control Hub. The layered structure of rules reduces the need to replace an entire rule set with a new rule set when a change occurs (e.g., when an interference event occurs or when no interference event occurs), because individual routine rule layers can be deleted without affecting other routine rule layers.

[0026] Exemplary embodiments will now be described, by way of example only, with reference to the following drawings, in which: [Brief description of the drawings]

[0027] [Figure 1] FIG. 1 is a schematic diagram of a hub system. [Diagram 2] 1 is a flowchart illustrating a method for modifying a rule in a control hub according to an embodiment of the present disclosure. [Diagram 3] FIG. 2 is a block diagram illustrating a control hub according to an embodiment of the present disclosure. [Figure 4] FIG. 11 is a sequence diagram illustrating an example of a rule modification according to an embodiment of the present disclosure. [Diagram 5] FIG. 11 is a sequence diagram illustrating an example of a rule modification according to an embodiment of the present disclosure. [Figure 6] FIG. 11 is a sequence diagram illustrating an example of a rule modification according to an embodiment of the present disclosure. [Figure 7] FIG. 11 is a sequence diagram illustrating an example of a rule modification according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] As described above, an improved method for modifying rules stored in a control hub and a control hub that addresses existing problems are provided. In the following description, examples are described for electric toothbrushes and electric shavers, but it will be understood that the described method and control hub are applicable to other types of devices and equipment, such as personal grooming devices, cooking appliances, entertainment devices, etc. It will be understood how additional layers of rules can be generated for these other types of devices for usage scenarios related to user routines. Furthermore, in the following description, examples are described for voice control, but it will be understood that the described method and control hub are also applicable to scenarios where other types of control are used, such as on-screen interactions.

[0029] FIG. 2 is a flow chart illustrating a method for modifying rules in a control hub according to an embodiment of the present disclosure. The control hub is connected to one or more devices. The one or more devices include one or more of an electric toothbrush, an electric shaver, an oral cleaning device, an interdental device, a hair care device, a hair removal device, a skin care device, a body grooming device, an epilation device, an intense pulse light (IPL) device, and a body trimming device. The one or more devices also include non-personal devices such as lighting fixtures (e.g., ceiling lights, mirror lights, etc.) in the user's home environment. Furthermore, the control hub is configured to provide at least one of audio information and visual information, for example, via an auxiliary device (e.g., a connected tablet) or a user interface in the control hub. The control hub is a voice-assisted control hub (or sometimes referred to as a "voice-controlled" control hub).

[0030] The method begins with step 210 of obtaining a base routine rule layer for controlling one or more devices in a usage scenario. The base routine rule layer is based on historical data related to a user's routine. In some embodiments, obtaining the base routine rule layer in step 210 includes obtaining historical data related to a user's routine on at least one of the one or more devices and generating the base routine rule layer based on the obtained historical data.

[0031] Historical data related to a user's routine can be obtained or acquired from one or more sources, such as from a memory or cloud storage storing data of parameters detected by sensors or sensing mechanisms on one or more devices during one or more previous sessions (e.g., a previous treatment session or a previous grooming session) or during one or more previous portions of a current session. Additionally or alternatively, historical data can include usage data detected / obtained for the same particular user when operating other devices (i.e., devices not directly used during the routine), such as devices in the same application category. For example, in a routine using an electric toothbrush, (historical) usage data acquired on an interdental device for the same user can be acquired as historical data to generate a base routine rule layer. Additionally or alternatively, historical data can include (average) usage data detected / obtained for one or more other users when operating devices related to the routine and / or devices in the same application category.

[0032] Additionally or alternatively, the historical data may include situational data, such as data related to the user's physiological condition, such as beard length, data related to the user's oral health, data related to the user's skin condition, data related to weather conditions (e.g., air humidity), and comparative data related to the user's operating patterns with the device (e.g., labeled patterns of stroking movements of the device).

[0033] Returning to Figure 2, at step 220, at least one of sensor data and device data is obtained from at least one of the one or more devices. In some embodiments, the sensor data and / or device data is obtained in real-time, i.e., for immediate determination of interference events in a next step and subsequent generation of a new rule layer, as described in more detail below.

[0034] The sensor data may include device timer data, device motion sensor data, device accelerometer data, device rotation sensor data, device angle sensor data (e.g., indicative of a change in the angle of a device accessory relative to a user's face, or a change in the angle of a device handle relative to a user's face / hand / arm, etc.), device battery level data, device pressure sensor (e.g., capacitive or resistive touch sensor, Hall sensor, or force sensor) data (e.g., indicative of the force with which an accessory or portion of the device is pressed against a user's skin or oral area), device stroke length sensor data, device stroke rate sensor data, device stroke density sensor data (e.g., indicative of the number of strokes in a given area of ​​a body part being treated), device touch sensor data (e.g., indicative of when an accessory or portion of the device has touched a user's skin), device interruption sensor data (e.g., indicative of an interruption of a treatment session on the device), device distance sensor data (e.g., data from a mirror, The device may include at least one of: device grip sensor data (e.g., indicative of a user's grip change and grip movement pattern), device hair density sensor data, device hair length sensor data, device environmental sensor data (e.g., indicative of air humidity level, skin moisture level, air temperature level, etc.), device displacement sensor data (e.g., indicative of a linear or rotational displacement of a device accessory relative to a device handle), device motion sensor data (e.g., indicative of cutting / driving activity at the device), device skin moisture sensor, device skin oil sensor, device skin pH sensor data, device pulse sensor data, device image sensor data (e.g., indicative of a user's gesture, indicative of skin zone information, indicative of a device stroke length and / or speed, etc.), and device accessory sensor data (e.g., indicative of a device accessory / accessory type, a device accessory / accessory usage, or a device accessory / accessory wear level). In some embodiments, the sensor data is categorized by session or routine. Detected interruptions, as indicated by, for example, interruption sensor data, are obtained for each session.

[0035] The device data includes at least one of the following: battery level status of the device, remaining time for an action (e.g., brushing) corresponding to the device (or an accessory of the device), cleanliness status of the device, wear status of the device, usage statistics related to the accessory of the device (e.g., quality metrics of linear and / or rotational movement for shaving or trimming), revolutions per minute (RPM) on the device (or an accessory of the device), torque level of the device, operating mode or function of the device, connectivity status of the device (e.g., "Bluetooth on / off"), time spent in a body zone of the device (e.g., face, oral zone, beard), and operation metrics of the device. In some embodiments, the device data is categorized by session or routine. For example, usage statistics related to accessories are obtained on a per-session basis.

[0036] 2, in step 230, it is determined whether there is an interference event based on evaluation of at least one of the sensor data and the device data. An interference event is an event that conflicts with the basic routine rule layer obtained in step 210.

[0037] For example, an interference event is when the detected pressure of a device accessory against the user's skin exceeds a predefined threshold and is therefore incompatible with the use of a particular operating mode of the device. As another example, an interference event is when an unergonomic body position or movement is detected (e.g., via a motion sensor, acceleration sensor, image sensor) and is therefore incompatible with the use of a particular device. As another example, an interference event is when the shaving behavior between the left and right halves of the user's face is determined to be different (e.g., a difference in pressure detected via a pressure sensor) and is therefore incompatible with the use of the same operating mode on both halves of the face. As another example, an interference event is when the detected use behavior of the device does not meet a required operating pattern (e.g., moving the device in a straight line vs. moving the device in a circular / curved line) and is therefore incompatible with the use sequence of the device (i.e., it is not desirable to proceed to the next part of the routine because the step is considered not completed).

[0038] Returning to Figure 2, in step 240, upon determining that there is an interference event, an additional routine rule layer is generated for controlling one or more devices in the usage scenario when an interference event occurs, the additional routine rule layer is generated based on at least one of the sensor data and the device data.

[0039] In some embodiments in which the control hub is connected to a plurality of devices (e.g., including an electric toothbrush and an electric shaver), the base routine layer determines a first relative priority of use of at least a subset of the plurality of devices, and the additional routine rule layer determines a second relative priority of use of at least a subset of the plurality of devices to respond to or avoid an interference event. In these embodiments, the second relative priority is different from the first relative priority.

[0040] To illustrate this with an example, in step 210, from historical data related to the user's routine, it can be derived as a basic routine rule layer that in the user's normal routine, the electric toothbrush is used before the electric shaver. Thus, in this example, the first relative priority of use (as determined by the rule layer of the basic routine) prioritizes the electric toothbrush over the electric shaver. Next, in steps 220 and 230, the control hub determines from the sensor data and / or device data (e.g., battery level data / status) that the current battery level of the electric toothbrush is too low to operate. That is, the interference event in this example is that the current battery level of the electric toothbrush is lower than a predetermined threshold. Thus, in step 240, when this interference event occurs, an additional routine rule layer is generated to determine a different relative priority of use to prioritize the use of the electric shaver before the electric toothbrush so as to ensure time to charge before using the electric toothbrush.

[0041] In some embodiments where the control hub is connected to multiple devices (e.g., including an electric trimmer and an electric razor), the basic routine rule layer determines a first device of the multiple devices to use in a usage scenario, and the additional routine rule layer determines a second device of the multiple devices to use in the usage scenario to respond to or avoid an interference event. In these embodiments, the second device is different from the first device.

[0042] To illustrate this with an example, in step 210, from historical data related to the user's routine, the basic routine rule layer can derive that the user's normal routine uses an electric trimmer to perform a beard trimming routine. Thus, in this example, the first device (as determined by the basic routine rule layer) is the electric trimmer. Then, in steps 220 and 230, the control hub determines from the sensor data and / or device data (e.g., cleanliness status / level or wear status / level) that the electric trimmer is not suitable for the beard trimming procedure, for example, because the electric trimmer needs to be cleaned and / or maintained in order to function properly. That is, the interference event in this example is that the current cleanliness / wear level is lower than a predefined threshold. Thus, in step 240, when this interference event occurs, an additional routine rule layer is generated to determine a different device (having similar functionality), such as an electric razor, to be used in the same procedure, so that the user can continue the routine using a different (suitable) device, rather than using an inappropriate device that may cause operational issues or skin problems.

[0043] In some embodiments, the basic routine rule layer determines a first operating mode for a device of one or more devices used in a usage scenario, and the additional routine rule layer can determine a second operating mode for a device used in the usage scenario to respond to or avoid an interference event, in these embodiments, the second operating mode is different from the first operating mode.

[0044] To illustrate this with an example, in step 210, from past data related to the user's routine, the basic routine rule layer can derive that the user's normal routine is to use the turbo mode in the electric shaver to perform the shaving routine. Thus, in this example, the first operating mode (as determined by the basic routine rule layer) is the turbo mode. Next, in steps 220 and 230, the control hub determines from the sensor data and / or device data (e.g., skin moisturization sensor data and skin oil sensor data) that the turbo mode is not suitable for the user's current skin health metric because it may cause skin redness or dryness. That is, the interference event in this example is that the user's skin health level (indicated by at least one of the skin moisturization and skin oil amount) exceeds the respective predetermined threshold. Thus, in step 240, when this interference event occurs, an additional routine rule layer is generated to determine to start a different (e.g., default) operating mode in the electric shaver during the shaving procedure so as not to damage the user's skin during the shaving procedure.

[0045] Although not shown in FIG. 2, in some embodiments, the method further includes, after generating the additional routine rule layer in step 240, executing the additional rule layer and storing the additional routine rule layer in a rules database in the Control Hub (where the base routine rule layer is already stored). For example, the additional rule layer is stored to be associated with a particular usage scenario and / or user routine. The additional routine rule layer is stored as a layer in addition to the base routine rule layer, since both layers are associated with the same usage scenario and / or user routine.

[0046] Thus, the generation of additional routine rule layers means that new "rules" or "rule layers" are created, e.g. by involving the user in real time and evaluating system parameters at run time. These rules are thus determined and generated via sensor data at hand, executed in real time situations, and stored in the rules database. This approach reduces the user's effort and reduces the computational effort / cost of the control hub the next time the same situation occurs. Furthermore, this approach may attempt to address deviations in the entire device / sensor ecosystem by creating new rules, e.g. with the user's approval. Deviations can be recognized by event triggers, so that the corresponding rules are called only when necessary. This is believed to reduce the usage of computational resources compared to correcting or modifying individual rules or complex rule systems.

[0047] In some cases, a user of one or more devices may have a routine. This means that the basic routine rule layer is always applied. However, another user of one or more devices may be associated with an interference event. This generates an additional routine rule layer for this user. The additional routine rule layer increases personalization for the user. However, the basic routine rule layer can still be used, such as when the interference event does not occur again or is no longer relevant. Thus, the routine rule layer for controlling one or more devices associated with the user can be personalized for the user. The Control Hub may use computational resources (e.g., storage and / or processing) to generate and / or store the additional routine rule layer. Storing the additional routine rule layer (e.g., in persistent non-volatile storage in the Control Hub) can reduce the need to repeat the processing effort used to initially create the additional routine rule layer (e.g., if the same interference event occurs again). Personalization of the routine rule layer in the Control Hub can reduce unnecessary processing and / or storage of the additional routine rule layer in a network that includes multiple Control Hubs (e.g., as opposed to deploying a single rule set to all users in the network). In some cases, this can reduce the need to temporarily store data about rules in volatile storage (e.g., random access memory) in the Control Hub, freeing up memory resources for other tasks in the Control Hub.

[0048] In these embodiments, the method further includes obtaining a user interaction to confirm acceptance of the additional routine rule layer. For example, the control hub is configured to output an audio file such as "Are you willing to accept the alternative option?" or utterance specific to the additional routine rule layer, the usage scenario, and / or the user routine, and receive a voice command such as "yes" or "accept" from the user. In these embodiments, the execution of the additional routine rule layer and the saving of the additional routine rule layer in the rules database may be performed only upon obtaining a user interaction to confirm acceptance of the additional routine rule layer.

[0049] 2 are described as being performed sequentially, it will be understood that in some embodiments, at least some of the steps in the illustrated method may be performed in a different order and / or at least some of the steps in the illustrated method may be performed simultaneously. Furthermore, in some embodiments, the method illustrated in FIG. 2 may be performed multiple times to generate multiple additional routine rule layers (for the same or different basic routine rule layers).

[0050] The appropriate steps, methods, or functions may be performed through a computer program product that may be executed, for example, by the components and equipment illustrated in Figure 3. The computer program includes instructions that cause a processing circuit (and / or any operatively coupled entities and devices) to perform the methods according to the embodiments described herein. Thus, the computer program and / or computer program product provides means for performing the steps disclosed herein.

[0051] 3 is a block diagram illustrating a control hub according to an embodiment of the present disclosure. The control hub 300 is connected to one or more devices (not shown), such as one or more of an electric toothbrush, an electric shaver, an oral cleaning device, an interdental device, a hair care device, a hair removal device, a skin care device, a body grooming device, an epilation device, an intense pulsed light (IPL) device, and a body trimming device. The control hub 300 includes a processing circuit 310 and, optionally, a memory 320. The processing circuit 310 is configured to provide at least one of audio and visual information, for example, via an auxiliary device (e.g., a connected tablet) or a user interface at the control hub 300. In some embodiments, the control hub is a voice-assisted control hub (or may be referred to as a "voice-controlled" control hub).

[0052] Further, the processing circuitry 310 is configured to obtain a base routine rule layer for controlling the one or more devices in a usage scenario. The base routine rule layer is based on historical data related to a user's routine. In some embodiments, the processing circuitry 310 is configured to obtain the base routine rule layer by obtaining historical data related to a user's routine on at least one of the one or more devices and generating the base routine rule layer based on the obtained historical data.

[0053] Historical data related to a user's routine can be obtained or acquired from one or more sources, such as from a memory or cloud storage storing data of parameters detected by sensors or sensing mechanisms on one or more devices during one or more previous sessions (e.g., a previous treatment session or a previous grooming session) or during one or more previous portions of a current session. Additionally or alternatively, historical data can include usage data detected / obtained for the same particular user when operating other devices (i.e., devices not directly used during the routine), such as devices in the same application category. For example, in a routine using an electric toothbrush, (historical) usage data acquired on an interdental device for the same user can be acquired as historical data to generate a base routine rule layer. Additionally or alternatively, historical data can include (average) usage data detected / obtained for one or more other users when operating devices related to the routine and / or devices in the same application category.

[0054] Additionally or alternatively, the historical data may include situational data, such as data related to the user's physiological condition, such as beard length, data related to the user's oral health, data related to the user's skin condition, data related to weather conditions (e.g., air humidity), and comparative data related to the user's operating patterns with the device (e.g., labeled patterns of stroking movements of the device).

[0055] The processing circuit 310 is further configured to acquire at least one of sensor data and device data from at least one of the one or more devices, in some embodiments, the sensor data and / or device data is acquired in real-time, i.e., for immediately determining interference events in a next step and subsequently generating a new rule layer, as described in more detail below.

[0056] The sensor data includes at least one of: timer data of the device, motion sensor data of the device, accelerometer data of the device, rotation sensor data of the device, angle sensor data of the device, battery level data of the device, pressure sensor data of the device, stroke length sensor data of the device, stroke rate sensor data of the device, stroke density sensor data of the device, touch sensor data of the device, interruption sensor data of the device, distance sensor data of the device, grip sensor data of the device, hair density sensor data of the device, hair length sensor data of the device, environmental sensor data of the device, displacement sensor data of the device, motion sensor data of the device, skin moisture sensor of the device, skin oil sensor of the device, skin pH sensor data of the device, pulse sensor data of the device, image sensor data of the device, and accessory sensor data of the device. In some embodiments, the sensor data is classified by session or routine. For example, detected interruptions indicated by interruption sensor data are obtained for each session.

[0057] The device data includes at least one of the following: battery level status of the device, remaining time for an action corresponding to the device (or an accessory of the device), cleanliness status of the device, wear status of the device, usage statistics related to an accessory of the device, revolutions per minute (RPM) on the device (or an accessory of the device), torque level of the device, operating mode or function of the device, connectivity status of the device, time spent in a body zone of the device, and operational metrics of the device. In some embodiments, the device data is categorized by session or routine. For example, usage statistics related to accessories are obtained for each session.

[0058] The processing circuit 310 is configured to determine whether there is an interference event (an interference event being an event that conflicts with the basic routine rule layer) based on an evaluation of at least one of the sensor data and the device data, and upon determining that there is an interference event, generate an additional routine rule layer for controlling one or more devices in the usage scenario when an interference event occurs, the additional routine rule layer being generated based on at least one of the sensor data and the device data.

[0059] In some embodiments in which the control hub is connected to a plurality of devices (e.g., including an electric toothbrush and an electric shaver), the base routine layer determines a first relative priority of use of at least a subset of the plurality of devices, and the additional routine rule layer determines a second relative priority of use of at least a subset of the plurality of devices to respond to or avoid an interference event. In these embodiments, the second relative priority is different from the first relative priority.

[0060] In some embodiments where the control hub is connected to multiple devices (e.g., including an electric trimmer and an electric razor), the basic routine rule layer determines a first device of the multiple devices to use in a usage scenario, and the additional routine rule layer determines a second device of the multiple devices to use in the usage scenario to respond to or avoid an interference event. In these embodiments, the second device is different from the first device.

[0061] In some embodiments, the basic routine rule layer determines a first operating mode for a device of one or more devices used in a usage scenario, and the additional routine rule layer can determine a second operating mode for a device used in the usage scenario to respond to or avoid an interference event, in these embodiments, the second operating mode is different from the first operating mode.

[0062] In some embodiments, the processing circuitry 310 is configured to generate the additional routine rule layer, execute the additional rule layer, and store the additional routine rule layer in a rules database in the control hub. For example, the additional rule layer is stored to be associated with a particular usage scenario and / or user routine. The additional routine rule layer is stored as a layer in addition to the basic routine rule layer, since both layers are associated with the same usage scenario and / or user routine.

[0063] In some embodiments, the processing circuit 310 is configured to determine whether the additional acquired sensor data and / or device data indicates that an interference event has occurred after generating an additional layer of routine rules.

[0064] In this regard, the processing circuit 310 is configured to select the basic routine rule layer from the rule database in response to determining that no interference event has occurred after generating the additional routine rule layer based on additional acquired sensor data and / or device data.

[0065] On the other hand, the processing circuit 310 is configured to select an additional routine rule layer from the rule database in response to a determination that an interference event has occurred after generating the additional routine rule layer based on additional acquired sensor data and / or device data.

[0066] Depending on the selected routine rule layer, the processing circuitry 310 is configured to direct the "selected" basic or additional routine rule layer to be executed and to control one or more devices in accordance with the selected basic or additional routine rule layer.

[0067] In some cases, it may be computationally simple to implement and use a rule layer structure that includes a base routine rule layer and an additional routine rule layer. For example, rather than implementing a single large and complex rule set to control one or more devices, one of the base and additional routine rule layers may be selected to execute (e.g., to control one or more devices according to the selected routine rule layer). In some cases, separating rules into routine rule layers may facilitate quick access, processing, and implementation of individual routine rule layers (e.g., without executing the entire rule set).

[0068] In some embodiments, after generating the additional routine rule layer, the processing circuit 310 is configured to determine whether the additional routine rule layer still applies based on whether an interference event has occurred within a specified time period. The processing circuit 310 is further configured to remove the additional routine rule layer from the rules database in response to determining that an interference event has not occurred within the specified time period.

[0069] In some cases, unused or irrelevant routine rule layers may be deleted (e.g., after a specified period of time) to free up memory in the Control Hub. The layered structure of rules allows individual routine rule layers to be deleted without affecting other routine rule layers, reducing the need to replace an entire rule set with a new rule set when a change occurs (e.g., when an interference event occurs or when no interference event occurs).

[0070] In any of these embodiments, the processing circuitry 310 is further configured to obtain user interaction to confirm acceptance of the additional routine rule layer. For example, the control hub is configured to output an audio file such as "Are you willing to accept the alternative option?" or utterance specific to the additional routine rule layer, usage scenario, and / or user routine, and receive a voice command such as "yes" or "accept" from the user. In these embodiments, the execution of the additional routine rule layer and the saving of the additional routine rule layer in the rules database can be performed by the processing circuitry 310 only after obtaining user interaction to confirm acceptance of the additional routine rule layer.

[0071] It will be understood that FIG. 3 illustrates only the components necessary to illustrate one embodiment of control hub 300, and that in an actual implementation, control hub 300 may include components in place of or in addition to those illustrated.

[0072] For example, in some embodiments, the control hub 30 may further include a power source and / or a user interface. The user interface may be used to provide information resulting from the techniques described herein to a user of the control hub 300. Alternatively or additionally, the user interface may be configured to receive user input. For example, the user interface may be used to allow a user of the control hub 300 to confirm consent to an additional layer of routine rules. The user interface may be any user interface that allows information to be rendered (or output or displayed) to a user of the control hub 300. Alternatively or additionally, the user interface may be any user interface that allows a user of the control hub 300 to provide user input, interact with, or control the control hub 300. For example, the user interface may include one or more switches, one or more buttons, a keypad, a keyboard, a touch screen (e.g., on a tablet or smartphone) or an application, a display screen, a graphical user interface (GUI) or other visual rendering component, one or more speakers, one or more microphones or any other audio component, one or more lights, a component that provides haptic feedback (e.g., a vibration function) or any other user interface, or a combination of user interfaces.

[0073] 4 is a sequence diagram illustrating an example of rule modification according to an embodiment of the present disclosure. In this example, a user 410, an electric toothbrush 420, an electric shaver 430, a voice-assisted hub 440, and a digital platform 450 are provided. The voice-assisted hub 440 and the digital platform 450 can be collectively considered a single control hub (such as the control hub 300 described with reference to FIG. 3 above).

[0074] The method in this example begins at step S461, where the user 410 interacts with the electric toothbrush 420, e.g., picking up the electric toothbrush in preparation for a brushing session. Next, at step S462, the electric toothbrush 420 (connected to the voice-assisted hub 440) is awakened from sleep mode by the user 410's pick-up action and sends a notification to the voice-assisted hub 440. The notification includes sensor data and / or device data (e.g., usage statistics of the electric toothbrush 420).

[0075] Then, in steps S463 and S464, the voice assist hub 440 determines whether an interference event has occurred based on the notification received from the electric toothbrush 420 (the interference event conflicts with the basic routine rule layer stored in the digital platform 450), and after determining that an interference event has occurred, sends information related to the interference event to the digital platform 450. Next, in step S465, the digital platform 450 determines an additional routine rule layer based on the stored settings (which may include user profile preferences such as audio tones to be used in the voice assist hub) and sensor / device data, and in step S466, sends a first corresponding audio file to be output to the voice assist hub 440. The first corresponding audio file is an audio file corresponding to a response provided to the user 410 based on the current situation (e.g., of the electric toothbrush or bathroom environment).

[0076] Next, in step S467, the user 410 interacts with the power shaver 430, e.g., uses it in a shaving session. In step S468, the power shaver 430 (connected to the voice assist hub 440) sends a notification to the voice assist hub 440, which may include sensor data and / or device data (e.g., usage statistics of the power shaver 430).

[0077] Similarly, in step S469, the voice assist hub 440 determines whether an interference event has occurred based on the notification received from the electric shaver 430 (the interference event conflicts with the basic routine rule layer stored in the digital platform 450). In step S470, the voice assist hub monitors the connected device and provides real-time feedback (e.g., obtains an audio file saying "You're pressing too hard" when the pressure detected by the device is above a predetermined threshold). Then, in step S471, the voice assist hub 440 sends information related to the interference event to the digital platform 450 after determining that an interference event has occurred. Then, in step S472, the digital platform 450 determines an additional routine rule layer based on the stored settings (which may include user profile preferences such as audio tones to use in the voice assist hub) and sensor / device data, and in step S473, sends a second corresponding audio file to be output to the voice assist hub 440. The second corresponding audio file is an audio file corresponding to a response provided to the user based on the current situation.

[0078] In this example, the additional layers of routine rules determined in S465 and / or S472 may determine the priority of device usage and accordingly the output of audio files corresponding to those devices. Thus, in step S474, audio files determined to have a higher priority are output by the voice assist hub 440, and then in step S475, audio files determined to have a lower priority are output by the voice assist hub 440.

[0079] 5 is a sequence diagram illustrating an example of rule modification according to an embodiment of the present disclosure. In this example, a user 510, an electric toothbrush 520, an electric shaver 530, and a control hub represented by a hub component 540 and a voice assistant component 550 are provided.

[0080] The exemplary method begins at step S561, where the user 510 initiates a routine by issuing the command "Turn on toothbrush." ​​This command is received by the control hub's voice assistant component 550, which then invokes the stored basic routine rule layer at step S562. This basic routine rule layer determines that in the user's normal routine, the electric toothbrush 520 is used before the electric shaver 530 is used. Next, at step S563, the hub component 540 receives battery level data from both the electric toothbrush 520 and the electric shaver 530, analyzes the battery levels at step S564, and determines at step S565 that there is an interference event that conflicts with the basic routine rule layer. That is, it determines that the electric toothbrush 520 cannot be used before the electric shaver 530 because the current battery level of the electric toothbrush 520 is too low for operation.

[0081] Next, the voice assistant component 550 generates an additional routine rule layer ("For the routine, when the battery level is low, change the order of device use based on the measured parameters") based on the sensor and / or device data of the electric toothbrush 520 and / or the electric shaver 530, and requests the user 510's confirmation of the additional routine rule layer by outputting audio information "Shaver first, then toothbrush?" in step S566. When the voice assistant component 550 receives the confirmation in step S567 (i.e., the user says "yes"), it invokes the additional routine rule layer by turning on the electric shaver 530 in step S568.

[0082] 6 is a sequence diagram illustrating an example of rule modification according to an embodiment of the present disclosure. In this example, a user 7610, an electric trimmer 620, an electric shaver 630, and a control hub represented by a hub component 640 and a voice assistant component 650 are provided.

[0083] The exemplary method begins at step S661, where the user 610 initiates the routine by issuing the command "activate trimmer for facial hair routine." This command is received by the control hub's voice assistant component 650, which then invokes the stored basic routine rule layer at step S662. The basic routine rule layer determines that the electric trimmer 620 is to be used in the user's normal routine for facial hair grooming. Next, at step S663, the hub component 640 receives cleanliness and wear level data from both the electric trimmer 620 and the electric razor 630, and at step S664, analyzes the cleanliness and wear level data to determine that there is an interference event that conflicts with the basic routine rule layer. That is, the wear level and / or cleanliness of the electric trimmer 620 exceeds a predetermined threshold, and the electric trimmer 620 cannot be used to trim facial hair because it requires maintenance or cleaning.

[0084] Next, the voice assistant component 650 generates an additional routine rule layer ("When wear level and / or cleanliness exceed a predetermined threshold, use an alternative device based on the measured parameters") based on the sensor and / or device data of the electric trimmer 620 and / or the electric razor 630, and in step S665, requests the user 610 to confirm the additional routine rule layer by outputting audio information "The electric trimmer needs cleaning and maintenance, so please use the electric razor. Are you sure?". When the voice assistant component 650 receives the confirmation in step S666 (i.e., the user says "yes"), it calls the additional routine rule layer by turning on the electric razor 630 in step S667.

[0085] 7 is a sequence diagram illustrating an example of rule modification according to an embodiment of the present disclosure. In this example, a user 710, a power shaver 720, and a control hub represented by a hub component 730 and a voice assistant component 740 are provided.

[0086] The exemplary method begins at step S751, where the user 710 initiates a routine by issuing the command "Turn on shaver." This command is received by the voice assistant component 740 of the control hub, which then invokes the stored basic routine rule layer at step S752. This basic routine rule layer determines to use the electric shaver 720 for the user's normal routine shaving session. Next, at step S753, the hub component 730 receives skin moisture level data, skin oil amount data, and / or conductance sensor data from the electric shaver 720, and at step S754, analyzes the skin health metric based on the received data to determine that there is an interference event that conflicts with the basic routine rule layer. That is, it determines that the turbo mode is not suitable for the user's current skin health metric and that using the turbo mode may damage the user's skin.

[0087] Next, the voice assistant component 740 generates an additional routine rule layer ("When the user's skin health metrics indicate that the skin is in a sensitive state, use the shaver in the default mode based on the measured parameters") based on the sensor and / or device data of the electric shaver 720, and in step S755, requests the user 710 to confirm the additional routine rule layer by outputting audio information such as "Your skin seems to be sensitive today, so use the shaver in the default mode instead of the turbo mode. Is that OK?". When the voice assistant component 740 receives the confirmation in step S756 (i.e., the user says "yes"), it invokes the additional routine rule layer by turning on the electric shaver 720 in the default mode in step S757.

[0088] This disclosure includes subject matter defined by the following numbered paragraphs:

[0089] Section 1: 1. A computer-implemented method for modifying rules in a control hub, the control hub being connected to one or more devices and configured to provide at least one of audio information and visual information, the method comprising: obtaining a base routine rule layer for controlling one or more devices in a usage scenario, the base routine rule layer being based on historical data related to a user's routine; acquiring at least one of sensor data and device data from at least one or more devices; determining whether there is an interference event based on an evaluation of at least one of the sensor data and the device data, the interference event conflicting with a basic routine rule layer; generating, upon determining that there is an interference event, an additional routine rule layer based on at least one of the sensor data and the device data, the additional routine rule layer being for controlling one or more devices in the usage scenario when the interference event occurs; 13. A computer-implemented method comprising:

[0090] Section 2: The step of obtaining a basic routine rule layer for controlling one or more devices includes: acquiring, at at least one of the one or more devices, historical data relating to a user's routine; generating a basic routine rule layer based on the acquired past data; Item 1. The computer-implemented method of item 1, comprising:

[0091] Section 3: After generating the additional routine rule layer, executing an additional layer of routine rules; storing an additional layer of routine rules in the rules database of the Control Hub; 3. The computer-implemented method of claim 1 or 2, further comprising:

[0092] Section 4: The computer-implemented method of claim 3, further comprising the step of obtaining user interaction to confirm compliance with the additional routine rule layer, wherein the steps of executing the additional routine rule layer and saving the additional routine rule layer are performed only when user interaction to confirm compliance with the additional routine rule layer is obtained.

[0093] Section 5: 5. The computer-implemented method of any one of claims 1 to 4, wherein the control hub is connected to a plurality of devices, the basic routine rule layer determines a first relative priority of use of at least a subset of the plurality of devices, and the additional routine rule layer determines a second relative priority of use of at least a subset of the plurality of devices to respond to or avoid an interference event, the second relative priority of use being different from the first relative priority of use.

[0094] Item 6: 5. The computer-implemented method of any one of claims 1 to 4, wherein the control hub is connected to a plurality of devices, the basic routine rule layer determines a first device of the plurality of devices to be used in a usage scenario, and the additional routine rule layer determines a second device of the plurality of devices to be used in the usage scenario to respond to or avoid an interference event, the second device being different from the first device.

[0095] Section 7: 5. The computer-implemented method of any one of claims 1 to 4, wherein the basic routine rule layer determines a first operating mode for a device among one or more devices used in the usage scenario, and the additional routine rule layer determines a second operating mode for a device used in the usage scenario to respond to or avoid an interference event, the second operating mode being different from the first operating mode.

[0096] Section 8: 8. The computer-implemented method of any one of clauses 1 to 7, wherein the sensor data includes at least one of device time data, device motion sensor data, device accelerometer data, device rotation sensor data, device angle sensor data, device battery level data, device pressure sensor data, device stroke length sensor data, device stroke rate sensor data, device stroke density sensor, device touch sensor data, device interruption sensor data, device distance sensor data, device grip sensor data, device hair density sensor data, device hair length sensor data, device environmental sensor data, device displacement sensor data, device motion sensor data, device skin moisture sensor, device skin oil sensor, device skin pH sensor data, device pulse sensor data, device image sensor data, and device accessory sensor data.

[0097] Section 9: The computer-implemented method of any one of clauses 1 to 8, wherein the device data includes at least one of the following: battery level status of the device, remaining time for an action corresponding to the device, cleanliness status of the device, wear status of the device, usage statistics related to accessories of the device, revolutions per minute (RPM) of the device, torque level of the device, operating mode or function of the device, connectivity status of the device, time spent in a body zone of the device, and operational metrics of the device.

[0098] Section 10: The computer-implemented method of claim 8, wherein the sensor data includes at least one of skin moisturization sensor data of the device and skin oil amount sensor data of the device, and the interference event occurs when the user's skin moisturization level or the user's skin oil amount exceeds a predetermined threshold.

[0099] Section 11: The computer-implemented method of claim 8 or 9, wherein the sensor data includes battery level data of the device and / or the device data includes a battery level status of the device, and the interference event occurs when the battery level of the device is below a predetermined threshold or when the battery level of the device is lower than the battery level of another device connected to the control hub.

[0100] Section 12: 10. The computer-implemented method of claim 9, wherein the device data includes a cleanliness status of the device, and the interference event occurs when the cleanliness status of the device is below a predetermined threshold.

[0101] Section 13: 13. The computer-implemented method of any one of claims 1 to 12, wherein the one or more devices include one or more of an electric toothbrush, an electric shaver, an oral cleaning device, an interdental device, a hair care device, a hair removal device, a skin care device, a body grooming device, an epilation device, an intense pulsed light (IPL) device, and a body trimming device.

[0102] Section 14: 14. A computer program comprising a computer readable medium, the computer readable medium having computer readable code embodied therein, the computer readable code being configured, when executed by a suitable computer or processor, to cause the computer or processor to perform the computer implemented method of any one of claims 1 to 13.

[0103] Section 15: a control hub connected to one or more devices and providing at least one of audio and visual information; obtaining a base routine rule layer for controlling one or more devices in a usage scenario, the base routine rule layer being based on historical data related to a user's routine; acquiring at least one of sensor data and device data from at least one of the one or more devices; determining whether there is an interference event based on an evaluation of at least one of the sensor data and the device data, the interference event conflicting with a basic routine rule layer; and upon determining that there is an interference event, generating an additional routine rule layer based on at least one of the sensor data and the device data, the additional routine rule layer being for controlling one or more devices in the usage scenario when the interference event occurs.

[0104] As used herein, the phrase "at least one" followed by a recited set of elements or features refers to any number or combination of the recited set of elements or features. For example, when the phrase "at least one" is used, it can refer to "one" or "more than one" of the recited set of elements or features. In other words, for a recited set of elements / features: A, B, and C, the phrase "at least one of A, B, and C" means "A, B, and / or C," e.g., only B is sufficient.

[0105] Variations of the disclosed embodiments can be understood and effected by those skilled in the art in practicing the principles and techniques described herein, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word "comprises" does not exclude other elements or steps, and the singular elements do not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain means are recited in mutually different dependent claims does not indicate that a combination of these means cannot be used to advantage. A computer program can be stored or distributed on any suitable medium, such as an optical storage medium or a solid-state medium, supplied together with or as part of other hardware, but can also be distributed in other forms, such as via the Internet or other wired or wireless communication systems. Any reference signs in the claims should not be interpreted as limiting the scope.

Claims

1. 1. A computer-implemented method for modifying rules in a control hub, the control hub connected to one or more devices providing at least one of audio and visual information, the method comprising: obtaining a base routine rule layer for controlling the one or more devices in a usage scenario, the base routine rule layer being based on historical data related to a user's routine; acquiring at least one of sensor data and device data from the at least one device; determining whether there is an interference event based on an evaluation of the at least one of the sensor data and the device data, the interference event conflicting with the basic routine rule layer; generating an additional routine rule layer based on the at least one of the sensor data and the device data upon determining that there is an interference event, the additional routine rule layer being for controlling the one or more devices in the usage scenario when the interference event occurs; determining whether additional acquired sensor data and / or device data indicates that the interference event occurred after generating the additional routine rule layer; selecting the basic routine rule layer from the rule database in response to determining that the interference event has not occurred after generating the additional routine rule layer based on the additional acquired sensor data and / or device data; or selecting the additional routine rule layer from the rule database in response to determining that the interference event has occurred after generating the additional routine rule layer based on the additional acquired sensor data and / or device data; instructing execution of the selected basic or additional routine rule layer to control the one or more devices in accordance with the selected basic or additional routine rule layer; executing said additional routine rule layer; storing the additional routine rule layer in a rules database of the control hub; 13. A computer-implemented method comprising:

2. The step of obtaining the basic routine rule layer for controlling the one or more devices includes: acquiring, on at least one of the one or more devices, the historical data associated with the routine of the user; generating the basic routine rule layer based on the acquired past data; 2. The computer-implemented method of claim 1, comprising:

3. After generating the additional routine rule layer, the method further comprises: determining whether the additional routine rule layer still applies based on whether the interference event occurred within a specified time period; removing the additional routine rule layer from the rule database in response to determining that the interference event has not occurred within the specified time period; 3. The computer-implemented method of claim 1, comprising:

4. 4. The computer-implemented method of claim 1, further comprising the step of obtaining a user interaction to confirm consent to the additional routine rule layer, wherein the steps of executing the additional routine rule layer and saving the additional routine rule layer are performed only when the user interaction to confirm consent to the additional routine rule layer is obtained.

5. 5. The computer-implemented method of claim 1, wherein the control hub is connected to a plurality of devices, the basic routine rule layer determines a first relative priority of use of at least a subset of the plurality of devices, and the additional routine rule layer determines a second relative priority of use of at least the subset of the plurality of devices to respond to or avoid the interference event, the second relative priority of use being different from the first relative priority of use.

6. 5. The computer-implemented method of claim 1, wherein the control hub is connected to a plurality of devices, the basic routine rule layer determines a first device of the plurality of devices to be used in the usage scenario, and the additional routine rule layer determines a second device of the plurality of devices to be used in the usage scenario to respond to or avoid the interference event, the second device being different from the first device.

7. 5. The computer-implemented method of claim 1, wherein the basic routine rule layer determines a first operating mode for a device of the one or more devices used in the usage scenario, and the additional routine rule layer determines a second operating mode for the device used in the usage scenario to respond to or avoid the interference event, the second operating mode being different from the first operating mode.

8. 8. The computer-implemented method of claim 1, wherein the sensor data comprises at least one of device time data, device motion sensor data, device accelerometer data, device rotation sensor data, device angle sensor data, device battery level data, device pressure sensor data, device stroke length sensor data, device stroke rate sensor data, device stroke density sensor data, device touch sensor data, device interruption sensor data, device distance sensor data, device grip sensor data, device hair density sensor data, device hair length sensor data, device environment sensor data, device displacement sensor data, device motion sensor data, device skin moisture sensor data, device skin oil sensor data, device skin pH sensor data, device pulse sensor data, device image sensor data, and device accessory sensor data.

9. 9. The computer-implemented method of claim 1, wherein the device data includes at least one of a battery level status of the device, a remaining time for an action corresponding to the device, a cleanliness status of the device, a wear status of the device, usage statistics related to an accessory of the device, revolutions per minute (RPM) of the device, a torque level of the device, an operating mode or function of the device, a connectivity status of the device, a time spent in a body zone of the device, and an operational metric of the device.

10. 9. The computer-implemented method of claim 8, wherein the sensor data includes at least one of device skin moisture sensor data and device skin oil sensor data, and the interference event occurs when the user's skin moisture level or the user's skin oil level exceeds a predetermined threshold.

11. 10. The computer-implemented method of claim 8 or 9, wherein the sensor data includes battery level data of a device and / or the device data includes a battery level status of a device, and the interference event occurs when the battery level of the device is below a predetermined threshold or when the battery level of the device is lower than a battery level of another device connected to the control hub.

12. 10. The computer-implemented method of claim 9, wherein the device data includes a cleanliness status of a device, and the interference event occurs when the cleanliness status of the device is below a predetermined threshold.

13. 13. A computer program comprising a computer readable medium having computer readable code embodied therein which, when executed by a suitable computer or processor, causes the computer or processor to perform the computer implemented method of any one of claims 1 to 12.

14. a control hub connected to one or more devices, the control hub comprising: a processing circuit for providing at least one of audio and visual information, the processing circuit comprising: obtaining a base routine rule layer for controlling the one or more devices in a usage scenario, the base routine rule layer being based on historical data related to a user's routine; acquiring at least one of sensor data and device data from at least one of the one or more devices; determining whether there is an interference event based on the evaluation of the at least one of sensor data and device data, the interference event conflicting with the basic routine rule layer; generating an additional routine rule layer based on the at least one of sensor data and device data upon determining that there is an interference event, the additional routine rule layer being for controlling the one or more devices in the usage scenario when the interference event occurs; determining whether additional acquired sensor data and / or device data indicates that the interference event occurred after generating the additional routine rule layer; selecting the basic routine rule layer from the rule database in response to determining that the interference event has not occurred after generating the additional routine rule layer based on the additional acquired sensor data and / or device data; or selecting the additional routine rule layer from the rule database in response to determining that the interference event has occurred after generating the additional routine rule layer based on the additional acquired sensor data and / or device data; instructing execution of the selected basic or additional routine rule layer to control the one or more devices in accordance with the selected basic or additional routine rule layer; executing said additional routine rule layer; storing the additional routine rule layer in a rules database of the control hub; Run the Control Hub.

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