Abstract: Embodiments are described for a pattern-based control system that learns and applies device usage patterns for identifying and disabling devices exhibiting abnormal usage patterns. The system can learn a user's normal usage pattern or can learn abnormal usage patterns, such as a typical usage pattern for a stolen device. This learning can include human or algorithmic identification of particular sets of usage conditions (e.g., locations, changes in settings, personal data access events, application events, IMU data, etc.) or training a machine learning model to identify usage condition combinations or sequences. Constraints (e.g., particular times or locations) can specify circumstances where abnormal pattern matching is enabled or disabled. Upon identifying an abnormal usage pattern, the system can disable the device, e.g., by permanently destroying a physical component, semi-permanently disabling a component, or through a software lock or data encryption.

Abstract: Methods and apparatuses for providing security notification based on biometric identifier are described, in which one or more biometric information of a person may be utilized to permit or prohibit the person to access the vehicle. As such, the person may not access (or operate) the vehicle without satisfying security measures based on his/her biometric identifier generated from various biological information collected from the person. When the person is not authorized to access the vehicle, the security measures may transmit a security notification to an owner of the vehicle (e.g., a mobile device of the owner, an account of the owner) such that the owner may take appropriate steps in response to receiving the security notification. Such a notification may include the biometric information of the person, other information collected from the sensing component, a set of options for the owner to select from, among others.

Abstract: Methods and apparatuses for a mobile device (e.g., a mobile phone) supporting virtual peripherals are described. The mobile device may include a projecting component configured to project images to external surfaces outside of the mobile device. In some cases, the mobile device may project an image of a document on a first external surface and an image of a keyboard on a second external surface. Moreover, the mobile device may include an imaging component to receive inputs based on sensing an input device overlaid on the projected image (e.g., the keyboard). Accordingly, the mobile device may function as a computer with an external monitor and a keyboard, virtually added to the mobile device. In some cases, the mobile device may serve two or more users or purposes at a time. For example, the mobile device may operate as an infotainment device of a vehicle.

Abstract: Methods and apparatuses for providing security notification based on biometric identifier are described, in which one or more biometric information of a person may be utilized to permit or prohibit the person to access the vehicle. As such, the person may not access (or operate) the vehicle without satisfying security measures based on his/her biometric identifier generated from various biological information collected from the person. When the person is not authorized to access the vehicle, the security measures may transmit a security notification to an owner of the vehicle (e.g., a mobile device of the owner, an account of the owner) such that the owner may take appropriate steps in response to receiving the security notification. Such a notification may include the biometric information of the person, other information collected from the sensing component, a set of options for the owner to select from, among others.

Abstract: Methods and apparatuses for arranging applications for a mobile device are described, in which the mobile device includes a set of applications. The mobile device may identify certain applications that a user of the mobile device is likely to activate, based on a particular environmental setting. The environmental setting may include a present location determined by a GPS, a present date and time, a present day, or the like. The mobile device may display graphical elements (e.g., icons) corresponding to the identified applications on a screen of the mobile device such that the user may conveniently activate the identified applications. In some embodiments, the mobile device may sort individual applications of the set based on quantities and/or lengths of activations to identify such applications. The mobile device may enlarge the icons by a predetermined factor before displaying them on the screen.

Abstract: Methods and apparatuses for emergency modes for a mobile device (e.g., a mobile phone) are described. The mobile device may receive sonic signals indicative of a voice of a person uttering words and identify the person as an authorized user. The mobile device may determine that the words correlate with an emergency situation from a set of predefined emergency situations. Further, the mobile device may determine that the emergency situation satisfies a threshold. The mobile device may perform one or more tasks (e.g., making a phone call to an emergency service), after determining that the emergency situation has satisfied the threshold. In some cases, the mobile device may monitor physiological signals of the person and/or collect additional data to increase a confidence level associated with making the determination. In some cases, the mobile device may leverage or include an artificial intelligence algorithm/engine to facilitate managing the emergency modes.

Abstract: Methods and apparatuses for a mobile device (e.g., a mobile phone) supporting virtual peripherals are described. The mobile device may include a projecting component configured to project images to external surfaces outside of the mobile device. In some cases, the mobile device may project an image of a document on a first external surface and an image of a keyboard on a second external surface. Moreover, the mobile device may include an imaging component to receive inputs based on sensing an input device overlaid on the projected image (e.g., the keyboard). Accordingly, the mobile device may function as a computer with an external monitor and a keyboard, virtually added to the mobile device. In some cases, the mobile device may serve two or more users or purposes at a time. For example, the mobile device may operate as an infotainment device of a vehicle.

Abstract: Methods and apparatuses for managing spoofed calls to a mobile device are described, in which the mobile device receives a call transmitted over a cellular or mobile network. The call may include a set of information associated with the network, such as a geological location of a device that generated the call, a hardware device identifier corresponding to the device, an internet protocol (IP) address associated with the device, or a combination thereof. The mobile device may determine whether the call is spoofed or genuine based on the set of information. Subsequently, the mobile device may assist a user of the mobile device to manage the call, such as blocking the call from reaching the user, informing the user that the call is spoofed, facilitating the user to report the call as spoofed to an authority and/or a service provider of the network.

Abstract: Secure access to a vehicle is described, in which one or more biometric identifiers of a user may be utilized to enable the vehicle. The user may not operate the vehicle without satisfying security measures based on his/her biometric identifier generated from various biological traits. In some embodiments, an artificial engine and/or algorithm may be combined to facilitate the authentication process to determine whether the user is authorized to use the vehicle. The secure access features may also manage a list of biometric identifiers of the authorized users. In some instances, the secure access features may be temporarily disabled. Further, individual parts of the vehicle may be associated with a unique identifier of the vehicle (which may include a vehicle identification number), and/or may be configured to transmit their geological locations determined by a global positioning system (GPS).

Abstract: Embodiments are described for a pattern-based control system that learns and applies device usage patterns for identifying and disabling devices exhibiting abnormal usage patterns. The system can learn a user’s normal usage pattern or can learn abnormal usage patterns, such as a typical usage pattern for a stolen device. This learning can include human or algorithmic identification of particular sets of usage conditions (e.g., locations, changes in settings, personal data access events, application events, IMU data, etc.) or training a machine learning model to identify usage condition combinations or sequences. Constraints (e.g., particular times or locations) can specify circumstances where abnormal pattern matching is enabled or disabled. Upon identifying an abnormal usage pattern, the system can disable the device, e.g., by permanently destroying a physical component, semi-permanently disabling a component, or through a software lock or data encryption.

Abstract: Embodiments for enabling or disabling application features according to application-specific security settings are described. The application-specific security settings can control when particular security levels, corresponding to authentication procedures, are required. The security levels can correspond to authentication procedures such as requiring no password, only requiring a PIN, allowing authentication by biometrics, or requiring a password. The application-specific security settings can control security levels based on a variety of circumstances such as setting particular security levels for particular locations, setting different security levels based on time since last device use, etc. In various implementations, the security levels can be mapped to application features to enable or disable.

Abstract: Methods and apparatuses for arranging applications for a mobile device are described, in which the mobile device includes a set of applications. The mobile device may identify certain applications that a user of the mobile device is likely to activate, based on a particular environmental setting. The environmental setting may include a present location determined by a GPS, a present date and time, a present day, or the like. The mobile device may display graphical elements (e.g., icons) corresponding to the identified applications on a screen of the mobile device such that the user may conveniently activate the identified applications. In some embodiments, the mobile device may sort individual applications of the set based on quantities and/or lengths of activations to identify such applications. The mobile device may enlarge the icons by a predetermined factor before displaying them on the screen.

Abstract: Methods and apparatuses for in-use charging for wearable devices are described, in which the wearable device may include an energy harvesting unit coupled with a rechargeable battery unit. The energy harvesting unit may include one or more transducers configured to generate electrical energy from various types of non-electrical energy around the wearable device such that the wearable device may replenish the rechargeable battery unit while a person uses the wearable devices. Such non-electrical energy may include electromagnetic energy, light energy, thermal energy, kinetic energy, or the like. Additionally, the rechargeable battery unit may include two or more partitions such that one of the partitions may be detached when necessary (e.g., to replace with a fully charged partition) without disrupting operations of the wearable device.

Abstract: Embodiments are described for a pattern-based control system that learns and applies device usage patterns for identifying and disabling devices exhibiting abnormal usage patterns. The system can learn a user's normal usage pattern or can learn abnormal usage patterns, such as a typical usage pattern for a stolen device. This learning can include human or algorithmic identification of particular sets of usage conditions (e.g., locations, changes in settings, personal data access events, application events, IMU data, etc.) or training a machine learning model to identify usage condition combinations or sequences. Constraints (e.g., particular times or locations) can specify circumstances where abnormal pattern matching is enabled or disabled. Upon identifying an abnormal usage pattern, the system can disable the device, e.g., by permanently destroying a physical component, semi-permanently disabling a component, or through a software lock or data encryption.

Abstract: Methods and apparatuses for arranging applications for a mobile device are described, in which the mobile device includes a set of applications. The mobile device may identify certain applications that a user of the mobile device is likely to activate, based on a particular environmental setting. The environmental setting may include a present location determined by a GPS, a present date and time, a present day, or the like. The mobile device may display graphical elements (e.g., icons) corresponding to the identified applications on a screen of the mobile device such that the user may conveniently activate the identified applications. In some embodiments, the mobile device may sort individual applications of the set based on quantities and/or lengths of activations to identify such applications. The mobile device may enlarge the icons by a predetermined factor before displaying them on the screen.

Abstract: Methods and apparatuses for in-use charging for wearable devices are described, in which the wearable device may include an energy harvesting unit coupled with a rechargeable battery unit. The energy harvesting unit may include one or more transducers configured to generate electrical energy from various types of non-electrical energy around the wearable device such that the wearable device may replenish the rechargeable battery unit while a person uses the wearable devices. Such non-electrical energy may include electromagnetic energy, light energy, thermal energy, kinetic energy, or the like. Additionally, the rechargeable battery unit may include two or more partitions such that one of the partitions may be detached when necessary (e.g., to replace with a fully charged partition) without disrupting operations of the wearable device.

Abstract: Methods and apparatuses for managing spoofed calls to a mobile device are described, in which the mobile device receives a call transmitted over a cellular or mobile network. The call may include a set of information associated with the network, such as a geological location of a device that generated the call, a hardware device identifier corresponding to the device, an internet protocol (IP) address associated with the device, or a combination thereof. The mobile device may determine whether the call is spoofed or genuine based on the set of information. Subsequently, the mobile device may assist a user of the mobile device to manage the call, such as blocking the call from reaching the user, informing the user that the call is spoofed, facilitating the user to report the call as spoofed to an authority and/or a service provider of the network.

Abstract: Methods and apparatuses for in-use charging for wearable devices are described, in which the wearable device may include an energy harvesting unit coupled with a rechargeable battery unit. The energy harvesting unit may include one or more transducers configured to generate electrical energy from various types of non-electrical energy around the wearable device such that the wearable device may replenish the rechargeable battery unit while a person uses the wearable devices. Such non-electrical energy may include electromagnetic energy, light energy, thermal energy, kinetic energy, or the like. Additionally, the rechargeable battery unit may include two or more partitions such that one of the partitions may be detached when necessary (e.g., to replace with a fully charged partition) without disrupting operations of the wearable device.

Abstract: Secure access to a vehicle is described, in which one or more biometric identifiers of a user may be utilized to enable the vehicle. The user may not operate the vehicle without satisfying security measures based on his/her biometric identifier generated from various biological traits. In some embodiments, an artificial engine and/or algorithm may be combined to facilitate the authentication process to determine whether the user is authorized to use the vehicle. The secure access features may also manage a list of biometric identifiers of the authorized users. In some instances, the secure access features may be temporarily disabled. Further, individual parts of the vehicle may be associated with a unique identifier of the vehicle (which may include a vehicle identification number), and/or may be configured to transmit their geological locations determined by a global positioning system (GPS).

Abstract: Methods and apparatuses for providing security notification based on biometric identifier are described, in which one or more biometric information of a person may be utilized to permit or prohibit the person to access the vehicle. As such, the person may not access (or operate) the vehicle without satisfying security measures based on his/her biometric identifier generated from various biological information collected from the person. When the person is not authorized to access the vehicle, the security measures may transmit a security notification to an owner of the vehicle (e.g., a mobile device of the owner, an account of the owner) such that the owner may take appropriate steps in response to receiving the security notification. Such a notification may include the biometric information of the person, other information collected from the sensing component, a set of options for the owner to select from, among others.