International Business Machines Corporation

Alyson T Cabral

James Xenidis

Brian Lee White Eagle

Karl J Weinmeister

Alexander J Buck

Christopher McCall Durham

Janani Mukundan

Richard B Daskas

Approaches presented herein enable performing a health analysis of a user using a smart floor mat. Specifically, a sensory array of the smart floor mat collects static and dynamic pressure data for capturing the movement and force exerted by a user's feet as the user walks across the smart floor mat. A healthcare analysis is then performed by comparing this current measurement data against the user's historical measurement data and expected results to generate a healthcare insight such as a trend, pattern, or deviation. The healthcare insight can predict or indicate a health issue. If a deviation exceeding a predefined permissible threshold exists, a healthcare professional can be notified.

Performing a health analysis using a smart floor mat

A method, system and computer program product for assisting a user to meet with other users with complementary attributes. Attributes (e.g., likes, dislikes) of a user, such as a user of a mobile device, are received to populate a profile of the user. The user attributes of profiles of actively participating users that are located in a geographic area are analyzed with respect to the attributes of the user to identify other users with complementary profiles. Those users with complementary profiles as the user are clustered to form a 'cluster' at a designated waypoint. Directions are then provided to the user to reach the designated waypoint to meet the other users of the same cluster. In this manner, the user is able to meet other users in the physical world with complementary interests and experiences at a designated waypoint.

Utilizing attributes of users to cluster users at a waypoint

An approach is provided in which an information handling system configures a reinforcement learning model based inspiration selections received from a user. The information handling system performs training iterations using the configured reinforcement learning model, which generates multiple actions and multiple rewards corresponding to multiple actions. The information handling system determines that the multiple rewards reach an empirical threshold and, in turn, generates a musical composition based on the multiple actions.

Composing music using foresight and planning

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Austin, TX, United States of America

Alyson T Cabral