Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Systems, apparatuses and methods for technology that provides smart work spaces in ubiquitous computing environments. The technology may determine a task to be performed in a smart work space and perform task modeling, wherein the task modeling includes determining one or more user interfaces involved with the task. One or more placements may be determined for the one or more user interfaces based on one or more ergonomic conditions, an incidence of an interaction, and a length of time of interaction. The technology may position the one or more user interfaces into the smart work space in accordance with the determined one or more placements.

Abstract: Systems, apparatuses and methods may provide for visually or audibly indicating to users what areas are being covered or monitored by cameras, microphones, motion sensors, capacitive surfaces, or other sensors. Indicators such as projectors, audio output devices, ambient lighting, haptic feedback devices, and augmented reality may indicate the coverage areas based on a query from a user.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Abstract: Systems, apparatuses and methods for technology that provides smart work spaces in ubiquitous computing environments. The technology may determine a task to be performed in a smart work space and perform task modeling, wherein the task modeling includes determining one or more user interfaces involved with the task. One or more placements may be determined for the one or more user interfaces based on one or more ergonomic conditions, an incidence of an interaction, and a length of time of interaction. The technology may position the one or more user interfaces into the smart work space in accordance with the determined one or more placements.

Abstract: Systems, devices, and techniques are provided for occupancy assessment of a vehicle. For one or more occupants of the vehicle, the occupancy assessment establishes position and/or identity for some or all of the occupant(s).

Abstract: Systems, apparatuses and methods may provide for visually or audibly indicating to users what areas are being covered or monitored by cameras, microphones, motion sensors, capacitive surfaces, or other sensors. Indicators such as projectors, audio output devices, ambient lighting, haptic feedback devices, and augmented reality may indicate the coverage areas based on a query from a user.

Abstract: Mobile device rejection of unintentional sensor contact. An embodiment of a mobile device includes a first touch sensor to detect contact by a user of the mobile device for input of gestures by the user, a memory to store indicators of unintentional contact to the first touch sensor, and a processor to evaluate contact to the first touch sensor. The processor compares a contact with the first touch sensor to the indicators of unintentional contact to determine if the contact is unintentional, and the mobile device rejects the contact as an input to the mobile device if the contact is determined to be unintentional and accepts the contact as an input to the mobile device if the contact is determined to be intentional.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Various systems and methods for remote multi-touch control are described herein. A system may include a mode controller to enter an orientation mode for a user interface displayed by a presentation device, the orientation mode configured to allow a user of the presentation device to orient an input point on the user interface with a remote device, and an input/output module to receive an input from the user to trigger the presentation device to transition from the orientation mode to a pass-through mode, the pass-through mode configured to allow the user to control an application at the presentation device using a touch point on the remote device, the mode controller is to enter the pass-through mode at the presentation device, the input/output module is to receive input from the user via the remote device, and the presentation device is to pass the input through to the application.

Abstract: A system for mapping user emotions includes a plurality of sensors for measuring user emotion indications and environmental data. A controller is coupled to the plurality of sensors. The controller reads the plurality of sensors to obtain at least one user emotion indication and environmental data coincident with the at least one user emotion indication. The controller further associates the environmental data with the user emotion indication.

Abstract: System and techniques secure group data exchange are described herein. A template may be obtained from local store. The template defines data segments and operations on data segments. A data segment definition may be extracted from the template. The data segment definition including a set of demographic values. An external store may be queried for external data segments with a definition including at least one demographic value from the set of demographic values. The data segments include an owner entity. A scenario may be executed in accordance with the template using a local data segment and the external data segments to produce an experimental result. The experimental result may be communicated to the owner entity.

Abstract: Techniques for gesture-based device connections are described. For example, a method may comprise receiving video data corresponding to motion of a first computing device, receiving sensor data corresponding to motion of the first computing device, comparing, by a processor, the video data and the sensor data to one or more gesture models, and initiating establishment of a wireless connection between the first computing device and a second computing device if the video data and sensor data correspond to gesture models for the same gesture. Other embodiments are described and claimed.

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Abstract: Systems and methods for receiving a communication on one or more user devices within a vehicle and redirecting the communications based at least in part on one or more user profiles associated with occupants of the vehicle is disclosed. The redirection of the communication may further be based at least in part on one or more sensor signals or a drive characteristic associated with the vehicle.

Abstract: Mobile device operation using grip intensity. An embodiment of a mobile device includes a touch sensor to detect contact or proximity by a user of the mobile device; a memory to store indicators of grip intensity in relation to the touch sensor; and a processor to evaluate contact to the touch sensor. The processor is to compare a contact with the touch sensor to the indicators of grip shape and firmness to determine grip intensity, and the mobile device is to receive an input for a function of the mobile device based at least in part on determined grip intensity for the mobile device.