Abstract: A system for a predictive claims computing platform may comprise a plurality of vehicles, a computing device associated with a repair facility, a network, and a server. The server may be configured to determine an insurance coverage type needed for repairing each vehicle in the plurality of vehicles, identify a location of the repair facility for repairing each vehicle, assign a standard amount to reimburse the repair facility for repairing each vehicle based on insurance coverage type and the location of the repair facility, transmit the standard amount to the computing device associated with the repair facility, receive from the computing device, a cost for actual repair of each vehicle after the actual repair for each vehicle has been completed, and adjust the standard amount to reimburse the repair facility for future repairs based on identifying a difference between the standard amount and the actual repair cost for each vehicle.

Abstract: Techniques to extract data from computer-readable purchase records of a user, cluster the items of interest based on descriptions of the items, and associate descriptive keywords to the clusters, where the keywords represent interests of the user. One or more processes and/or functions may be performed on extracted data, including cluster-specific processes and/or function, including user-based, user interest-based, and/or crowd-based processes and/or function, which may include shopping pattern extraction, item or types of items availability based on time, location and other contextual metric, pricing data of items and expected pricing changes over time and seasonal variations, identification of user preferences, and/or shopping recommendations.

Abstract: Selective/controlled disclosure of user information to private workspaces of other users/invitees based on context/contextual relations, and a shared workspace or market to collaborate amongst the other users (e.g., to crowd-source gifts of interest to the recipient). Contextual disclosure may be based on common context or commonality under a set of conditions, such as a topic, which may include known topics of relationships amongst the users and/or undiscovered contexts. As an example, items of interest to each user are identified and clustered, keywords are assigned to the clusters indicative of topics/subjects of interests to the respective users, recipient keywords are compared to keywords of an invitee to identify common keywords as shared interests, and items of interest to the recipient that relate to the common keywords are disclosed to the invitee as a personalized wish-list. Keyword weighting and/or keyword/item level privacy designations may be provided to further control disclosure.

Abstract: Technologies for immersive sensory experience sharing include one or more experience computing devices, an experience server, and a distance computing device. Each experience computing device captures sensor data indicative of a local sensory experience from one or more sensors and transmits the sensor data to the experience server. Sensors may include audiovisual sensors, touch sensors, and chemical sensors. The experience server analyzes the sensor data to generate combined sensory experience data and transmits the combined sensory experience data to the distance computing device. The experience server may identify one or more activities associated with the local sensory experience. The distance computing device renders a sensory experience based on the combined sensory experience data. The distance computing device may monitor a user response, generate user preferences based on the user response, and transmit the user preferences to the experience server. Other embodiments are described and claimed.

Abstract: In embodiments, apparatuses, methods and storage media (transitory and non-transitory) are described that receive sensor data from one or more sensor devices that depict a user gesture in three dimensional space, determine a flight path based at least in part on the sensor data, and store the flight path in memory for use to control operation of a drone. Other embodiments may be described and/or claimed.

Abstract: Technologies for motion-compensated virtual reality include a virtual reality compute device of a vehicle. The virtual reality compute device is configured to render a virtual reality content to an occupant of the vehicle and determine a motion of the vehicle based at least on sensor data generated by one or more vehicle motion sensors of the vehicle. Based on the determined motion of the vehicle, the virtual reality compute device modifies the rendered virtual reality media. In some embodiments, the virtual reality compute device may utilize other sensors associated with the vehicle and/or a user-worn virtual reality device to predict the motion of the vehicle in order to determine an expected motion of the vehicle that is expected to be sensed in the future.

Abstract: Technologies for establishing connections between or among people based at least in part on semantic distance and relational distance include one or more computing devices that analyze content created by computing device users, perform content clustering on the content, determine relational distances between connection candidates, and generate connection recommendations based at least in part on the content clustering and the relational distances.

Abstract: Technologies for motion-compensated virtual reality include a virtual reality compute device of a vehicle. The virtual reality compute device is configured to render a virtual reality content to an occupant of the vehicle and determine a motion of the vehicle based at least on sensor data generated by one or more vehicle motion sensors of the vehicle. Based on the determined motion of the vehicle, the virtual reality compute device modifies the rendered virtual reality media. In some embodiments, the virtual reality compute device may utilize other sensors associated with the vehicle and/or a user-worn virtual reality device to predict the motion of the vehicle in order to determine an expected motion of the vehicle that is expected to be sensed in the future.

Abstract: The present disclosure is directed to content protection for Data as a Service (DaaS). A device may receive encrypted data from a content provider via DaaS, the encrypted data comprising at least content for presentation on the device. For example, the content provider may utilize a secure multiplex transform (SMT) module in a trusted execution environment (TEE) module to generate encoded data from the content and digital rights management (DRM) data and to generate the encrypted data from the encoded data. The device may also comprise a TEE module including a secure demultiplex transform (SDT) module to decrypt the encoded data from the encrypted data and to decode the content and DRM data from the encoded data. The SMT and SDT modules may interact via a secure communication session to validate security, distribute decryption key(s), etc. In one embodiment, a trust broker may perform TEE module validation and key distribution.

Abstract: This disclosure is directed to a control system for user apparel selection. A system may comprise a control device to receive information from at least one sensor in an environment where apparel selection may commonly take place (e.g., closet). The control device may include communication circuitry, user interface circuitry, closet controller circuitry, etc. to receive user sensor data and apparel sensor data from the at least one sensor. Some or all of this data may be provided to at least one external resource such as, for example, an apparel designer, an apparel manufacturer, a feedback accumulation website, etc., to elicit at least styling data. Apparel control logic within the device may utilize the above data along with context data that describes, for example, the event for which the apparel is required, environmental data (e.g., weather), etc. to disposition apparel, suggest at least one piece of apparel to the person, etc.

Abstract: Examples are disclosed for determining a suggested camera pose or suggested camera settings for a user to capture one or more images. In some examples, the suggested camera pose or suggested camera settings may be based on an indication of the user's interest and gathered information associated with the user's interests. The user may be guided to adjust an actual camera pose or actual camera settings to match the suggested camera pose or suggested camera settings.

Abstract: Technologies for immersive sensory experience sharing include one or more experience computing devices, an experience server, and a distance computing device. Each experience computing device captures sensor data indicative of a local sensory experience from one or more sensors and transmits the sensor data to the experience server. Sensors may include audiovisual sensors, touch sensors, and chemical sensors. The experience server analyzes the sensor data to generate combined sensory experience data and transmits the combined sensory experience data to the distance computing device. The experience server may identify one or more activities associated with the local sensory experience. The distance computing device renders a sensory experience based on the combined sensory experience data. The distance computing device may monitor a user response, generate user preferences based on the user response, and transmit the user preferences to the experience server. Other embodiments are described and claimed.

Abstract: Embodiments of techniques, apparatuses, systems and computer-readable media for managing landscape of a property are disclosed. In some embodiments, a configuration module may be configured to receive data that specifies landscape or preferences for the landscape, and a sensor control module may configured to control operation of one or more sensors to record and report landscape associated operational data. In embodiments, a data aggregation and analysis module may be configured to receive environmental data for surroundings of the landscape and aggregate and analyze the environmental data, management preference data, and landscape data, and may cause appropriate irrigation to be provided to the landscape. Other embodiments may be disclosed and/or claimed.

Abstract: In embodiments, apparatuses, methods and storage media (transitory and non-transitory) are described that receive sensor data from one or more sensor devices that depict a user gesture in three dimensional space, determine a flight path based at least in part on the sensor data, and store the flight path in memory for use to control operation of a drone. Other embodiments may be described and/or claimed.

Abstract: Selective/controlled disclosure of user information to private workspaces of other users/invitees based on context/contextual relations, and a shared workspace or market to collaborate amongst the other users (e.g., to crowd-source gifts of interest to the recipient). Contextual disclosure may be based on common context or commonality under a set of conditions, such as a topic, which may include known topics of relationships amongst the users and/or undiscovered contexts. As an example, items of interest to each user are identified and clustered, keywords are assigned to the clusters indicative of topics/subjects of interests to the respective users, recipient keywords are compared to keywords of an invitee to identify common keywords as shared interests, and items of interest to the recipient that relate to the common keywords are disclosed to the invitee as a personalized wish-list. Keyword weighting and/or keyword/item level privacy designations may be provided to further control disclosure.

Abstract: Techniques to extract data from computer-readable purchase records of a user, cluster the items of interest based on descriptions of the items, and associate descriptive keywords to the clusters, where the keywords represent interests of the user. One or more processes and/or functions may be performed on extracted data, including cluster-specific processes and/or function, including user-based, user interest-based, and/or crowd-based processes and/or function, which may include shopping pattern extraction, item or types of items availability based on time, location and other contextual metric, pricing data of items and expected pricing changes over time and seasonal variations, identification of user preferences, and/or shopping recommendations.

Abstract: The present disclosure is directed to content protection for Data as a Service (DaaS). A device may receive encrypted data from a content provider via DaaS, the encrypted data comprising at least content for presentation on the device. For example, the content provider may utilize a secure multiplex transform (SMT) module in a trusted execution environment (TEE) module to generate encoded data from the content and digital rights management (DRM) data and to generate the encrypted data from the encoded data. The device may also comprise a TEE module including a secure demultiplex transform (SDT) module to decrypt the encoded data from the encrypted data and to decode the content and DRM data from the encoded data. The SMT and SDT modules may interact via a secure communication session to validate security, distribute decryption key(s), etc. In one embodiment, a trust broker may perform TEE module validation and key distribution.

Abstract: An image processing apparatus, system, and method to automatically determine a plurality of image acquisition settings for an scene; acquire a set of images of the scene, the set of images including multiple images acquired with a distinct plurality of the determined image acquisition settings; and generate a single image by combining the acquired set of images.

Abstract: Technologies for establishing connections between or among people based at least in part on semantic distance and relational distance include one or more computing devices that analyze content created by computing device users, perform content clustering on the content, determine relational distances between connection candidates, and generate connection recommendations based at least in part on the content clustering and the relational distances.

Abstract: Examples are disclosed for determining a suggested camera pose or suggested camera settings for a user to capture one or more images. In some examples, the suggested camera pose or suggested camera settings may be based on an indication of the user's interest and gathered information associated with the user's interests. The user may be guided to adjust an actual camera pose or actual camera settings to match the suggested camera pose or suggested camera settings.