Abstract: A method for input detection at a computing device includes receiving, from a camera, a plurality of images depicting a user hand. The plurality of images are processed to detect a plurality of user intent parameters, including a predefined activation gesture performed by the user hand. Responsive to the plurality of user intent parameters satisfying a gesture input activation condition, the plurality of images are processed to detect a movement of the user hand consistent with a predefined input gesture. The predefined input gesture is mapped to a computer control action, and the computer control action is performed in response to the predefined input gesture.

Abstract: Technologies for directional wayfinding include a mobile computing device having one or more local location sensors to generate data indicative of movement of the mobile computing device. The mobile computing device captures first sensor data indicative of movement of the mobile computing device along a path and determines a series of waypoints based on the first sensor data. The waypoints may describe movement data of the mobile computing device, including length and direction of movement. The mobile computing device determines a series of directional instructions to guide a user of the mobile computing device back along the path in the reverse order and presents the directional instructions to the user. The mobile computing device may monitor the sensor data to determine whether the user has arrived at each waypoint while reversing the path. The sensors may include an accelerometer, gyroscope, magnetometer, or altimeter. Other embodiments are described and claimed.

Abstract: This disclosure is directed to a context-aware proactive threat management system. In general, a device may use internal activity data along with data about external activities (e.g., provided by remote resources) for threat assessment and mitigation. A device may comprise, for example, a hostile environment detection (HED) module to coordinate threat assessment and mitigation. The HED module may accumulate internal activity data (e.g., from security services in the device), and external activity data regarding a system environment and/or a physical environment from the remote resources. The HED module may then assess threats based on the activity data and determine automated and/or manual mitigation operations to respond to the threats. In one embodiment, visualization features may also be used to, for example, visualize threats to a user, visualize automatic/manual mitigation operations, request user confirmation regarding the performance of manual mitigation operations, etc.

Abstract: Technologies for directional wayfinding include a mobile computing device having one or more local location sensors to generate data indicative of movement of the mobile computing device. The mobile computing device captures first sensor data indicative of movement of the mobile computing device along a path and determines a series of waypoints based on the first sensor data. The waypoints may describe movement data of the mobile computing device, including length and direction of movement. The mobile computing device determines a series of directional instructions to guide a user of the mobile computing device back along the path in the reverse order and presents the directional instructions to the user. The mobile computing device may monitor the sensor data to determine whether the user has arrived at each waypoint while reversing the path. The sensors may include an accelerometer, gyroscope, magnetometer, or altimeter. Other embodiments are described and claimed.

Abstract: Technologies for directional wayfinding include a mobile computing device having one or more local location sensors to generate data indicative of movement of the mobile computing device. The mobile computing device captures first sensor data indicative of movement of the mobile computing device along a path and determines a series of waypoints based on the first sensor data. The waypoints may describe movement data of the mobile computing device, including length and direction of movement. The mobile computing device determines a series of directional instructions to guide a user of the mobile computing device back along the path in the reverse order and presents the directional instructions to the user. The mobile computing device may monitor the sensor data to determine whether the user has arrived at each waypoint while reversing the path. The sensors may include an accelerometer, gyroscope, magnetometer, or altimeter. Other embodiments are described and claimed.

Abstract: This disclosure is directed to a context-aware proactive threat management system. In general, a device may use internal activity data along with data about external activities (e.g., provided by remote resources) for threat assessment and mitigation. A device may comprise, for example, a hostile environment detection (HED) module to coordinate threat assessment and mitigation. The HED module may accumulate internal activity data (e.g., from security services in the device), and external activity data regarding a system environment and/or a physical environment from the remote resources. The HED module may then assess threats based on the activity data and determine automated and/or manual mitigation operations to respond to the threats. In one embodiment, visualization features may also be used to, for example, visualize threats to a user, visualize automatic/manual mitigation operations, request user confirmation regarding the performance of manual mitigation operations, etc.

Abstract: A method, device, and system for generating a list of recipe recommendations includes determining the type and quantity of ingredients available to a user of a mobile computing device or smart storage. The available ingredients may be determined using text input or voice input from the user. A camera may also be used to capture images of the available ingredients for analysis. The list of recipes may be generated as a function of the type and quantity of available ingredient(s), meal preferences of the user, and the context of the meal. Recipe complements and/or supplements may be suggested in response to the user selecting a recipe from the list of recipe recommendations.