Abstract:
A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.
Abstract:
Users can switch between applications using contextual interface elements. These elements can include icons for applications determined to likely be accessed by the user for a current context. Information is gathered to determine the current context, then information such as patterns of historical usage are utilized to determine and rank the applications by likelihood of use. Different contexts can include different icons, and a given context can include different icons for different points in time or locations. A user can access a contextual interface element by performing a swipe motion, for example. The user can continue the motion to an area associated with an icon of interest, and perform an action such as a tap or release to cause the associated application to be launched. Such an approach enables a user to quickly and easily launch another application independent of the application currently active on the device.
Abstract:
Systems, methods, and computer-readable media are disclosed for generating a baseline use profile that indicates typical patterns of use of a device over time, transitioning the device to a challenge mode when sensor data indicates a deviation from the baseline use profile by more than a permissible tolerance, presenting challenges to the user while in the challenge mode, and determining whether to restrict or allow access to device functionality based on user responses to the challenges.
Abstract:
Approaches to enable a computing device, such as a phone or tablet computer, to compute a probability that the user currently using the device matches a profile of an authorized user and to set or change a security level of the computing device based on the computed probability. The security level can be one of many security levels each having a different scope of authorized access to data or functions of the computing device. The computing device may periodically re-compute the probability and change the security level whenever the probability crosses certain predefined thresholds.
Abstract:
Content is presented by media devices to a user. Described herein are techniques and systems for determining occurrence of one or more events at, or proximate to, the media device. Once an event is determined, one or more actions to modify presentation of the content may be initiated. The actions may include starting presentation of the content, stopping presentation of the content, applying noise mitigation techniques to the content, and so forth. The noise mitigation techniques may include modification of an intended signal from the content to produce a noise mitigation zone 118 proximate to, or encompassing, at least a portion of the user's head.
Abstract:
A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.
Abstract:
Described herein are systems, devices and methods for presenting content based on the spatial relationship between a media device and a user of the media device. The media device may present content based on an angle between an eye axis of the user and a device axis of the media device.
Abstract:
A computing device can obtain usage data associated with the device. The usage data indicate how the computing device operates or how the device is used. The device can analyze the usage data to recognize usage patterns. The usage patterns can correspond to recurring actions or tasks initiated by the user using the device, such as actions or tasks initiated due to the user's habits and/or routines. Based on the usage patterns, the device can determine a task that has a sufficient likelihood of being performed using the device within a specified or determined time (e.g., 5 minutes from now, one year from now, etc.). The device can provide information (e.g., recommendations) associated with the task, and likely relevant to the user. The user can use the provided information to perform the task, thereby increasing the ease of access or efficiency associated with performing the task.
Abstract:
Users may access a variety of content in many locations. Described herein are systems, devices and methods for introducing users that are in close proximity to one another. Historical location data of the media devices, data indicating content usage on the media devices, or a combination of the two is used to determine a correspondence between two or more users. Once the correspondence has been determined, an introduction may be provided.
Abstract:
Systems and approaches are provided for automating privacy control for a computing device based on a privacy or security context of the device. The privacy or security context of the computing device can be determined by analyzing sensor data or other input data captured by the device. The sensor and other input data can provide information such as a location of the computing device or the presence of other persons within the vicinity of the device to indicate whether the user is situated within a private or secure setting or a public or unsecure setting. A privacy or security control can be updated based on the determined privacy or security context, such as modifying a manner of displaying a pin or password during entry, elements of a home screen of the computing device, or preview content of user applications.