Abstract: Technologies for determining a heart rate of a user includes a wearable compute device having a heart rate sensor, a motion sensor, a heart rate determination manager, and a heart rate estimator. The wearable compute device generates sensor data indicative of a heart rate of the user and motion data indicative of a motion presently performed by the user. The wearable compute device determines whether to estimate the heart rate of the user based on the heart rate sensor data. The wearable compute device generates an estimated heart rate of the user using a heart rate estimation model and the motion data as an input to the heart rate estimation model in response to a determination to estimate the heart rate.

Abstract: A portable electronic device may generate a (RF) radio frequency fingerprint that includes information representative of at least a portion of RF signals received at a given physical location. The RF fingerprint may include, for example, a unique identifier and a signal strength that are both logically associated with at least a portion of the received RF signals. The portable electronic device may also receive data representative of a number of environmental parameters about the portable electronic device. These environmental parameters may be measured using sensors carried by the portable electronic device. Considered in combination, these environmental parameters provide an environmental signature for a given location. When combined into a data cluster, the RF fingerprint and the environmental signature may provide an indication of the physical subdivision where the portable electronic device is located.

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 technology that automatically detects a user reaction of a first occupant of a shared vehicle based on first data from one or more sensors associated with the shared vehicle. Additionally, the technology may automatically determine a root cause of the user reaction based on one or more of the first data or second data. In one example, co-occupant selection criteria associated with the first occupant is automatically updated if the root cause is a second occupant of the shared vehicle.

Abstract: Systems and methods may provide for a fitness sensor that is located and operates in a sensor hub. The fitness sensor may link to a Bluetooth link controller, a communications hub and numerous environmental and physical sensors in a platform that is conducive to low power utilization. Awakening a host processor only when valid content-oriented sensor data is available may assist to reduce a footprint of power consumption and time spent in computer processing fitness models.

Abstract: A system and method for device action and configuration based on user context detection from sensors in peripheral devices are disclosed. A mobile device includes an interface to receive sensor data from a sensor of a wearable peripheral device worn by a user. The mobile device further includes at least one processor to: identify an activity engaged in by the user based on the sensor data, detect a completion of the activity based on the sensor data, and configure the mobile device to generate a notification to the user in response to the detection of the completion of the activity.

Abstract: A technology is described for detecting a mechanical device. An example method may include retrieving magnetometer data generated by a magnetometer coupled to a mobile device. Magnetic features may be extracted from the magnetometer data, where the magnetometer data may be associated with magnetic field distortion patterns generated by mechanical motions of a mechanical device. Accelerometer data generated by an accelerometer coupled to the mobile device may be retrieved. Acceleration features associated with vibration patterns generated by the mechanical motions of the mechanical device may be extracted from the accelerometer data. Thereafter, the mechanical device may be identified using the magnetic features and the acceleration features.

Abstract: Computer systems to allow users to record sensor readings of their environment and correlate these sensor readings with mental health events for later analysis to improve mental health diagnoses and treatments. A monitoring system comprising a computing device and a sensor set (comprising one or more sensors integral to or communicatively coupled to the computing device) may collect and store data collected about the user. This data may be stored in the computing device, or may be stored in a cloud based data-storage service. This data may be annotated or correlated (either manually, or automatically) with mental health events of the user and used for later analysis.

Abstract: In some embodiments, the disclosed subject matter involves identifying environmental factors and user context that affect sleep quality. Embodiments use information about the static sleep environment, as well as dynamic environmental factors, such as sound, light, movement, correlated with user context, such as physical and emotional state, as well, as recent behavior to classify sleep data. The correlated and classified sleep data may be used to provide change recommendations, where implementing the recommended change is believed to improve the user's sleep quality. Other embodiments are described and claimed.

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: In some embodiments, the disclosed subject matter involves a system and method relating to improving the user experience of hearing, using an adaptable or adjustable hearing aid that takes environmental conditions into account when changing modes. A local server or gateway or cloud service iteratively analyzes the audio environment and feedback from the user to automatically change settings and mode of the user's hearing aid to improve hearing. Information from other users in similar audio environments may be used to assist in mode changes. Information about the audio environment, hearing aid settings/mode and user feedback may be correlated for future use by the user, or crowdsourced for other users, the hearing aid manufacturer or audiologist. Other embodiments are described and claimed.

Abstract: A portable electronic device may generate a (RF) radio frequency fingerprint that includes information representative of at least a portion of RF signals received at a given physical location. The RF fingerprint may include, for example, a unique identifier and a signal strength that are both logically associated with at least a portion of the received RF signals. The portable electronic device may also receive data representative of a number of environmental parameters about the portable electronic device. These environmental parameters may be measured using sensors carried by the portable electronic device. Considered in combination, these environmental parameters provide an environmental signature for a given location. When combined into a data cluster, the RF fingerprint and the environmental signature may provide an indication of the physical subdivision where the portable electronic device is located.

Abstract: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.

Abstract: Embodiments utilize a framework for modeling user's social roles in online self-expression tools such as blog or social networking, via semantic modeling techniques. The different ways users engage with content when stating explicit interests in their profile and via social expressions in a community are modeled. Certain themes guide the patterns users follow for expressing their interests in this community. An embodiment allows users to track how their posts and comments reflect with their online behavior. An embodiment infers the needs of the online community and makes suggestions or recommendations or sends alerts to users. Other embodiments are described and claimed.

Abstract: Systems, apparatuses and methods may leverage technology that generates textual descriptions of scenes based on visual content and audio content and generates haptic signals based on the textual descriptions if the textual descriptions satisfy a safety-related condition. Additionally, audio output signals may be generated based on the textual descriptions if the textual descriptions do not satisfy the safety-related conditions. In one example, a complex neural network (CNN) is trained and used to generate the textual descriptions in real-time.

Abstract: A system and method for device action and configuration based on user context detection from sensors in peripheral devices are disclosed. A mobile device includes an interface to receive sensor data from a sensor of a wearable peripheral device worn by a user. The mobile device further includes at least one processor to: identify an activity engaged in by the user based on the sensor data, detect a completion of the activity based on the sensor data, and configure the mobile device to generate a notification to the user in response to the detection of the completion of the activity.

Abstract: Technologies are presented that provide collaborative context-based user tracking and communications. A method of tracking communication options may include receiving, from one or more user devices of a user, user proximity information that indicates whether the user is in proximity of the one or more user devices; receiving, from the user devices, tracking loss warnings that indicate that loss of capabilities to track the user by respective user devices may be imminent; receiving, from the user devices, secondary device proximity information that indicates whether the user device is in proximity of one or more secondary devices; and receiving, from the secondary devices, additional user proximity information that indicates whether the user is in proximity of the one or more secondary devices. The method may further include dynamically determining from the received information which of the user devices and secondary devices are able to provide communications to the user.

Abstract: A portable consumer device, such as a mobile phone or a tablet computer, may be configured to collect measurements data associated with at least one of movement of the portable consumer device or orientation of the portable consumer device, as well as data associated with an external environment of the portable consumer device. The collected data may be evaluated in order to determine motion of the portable consumer device over time and contextual information associated with the portable consumer device. A user activity may be determined based upon the determined motion and the determined contextual information. As desired, the user activity may be evaluated in association with a suitable application scenario, such as a gaming application scenario.

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: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.