International Business Machines Corporation

Abhijit Singh

Anurag Srivastava

Manoj Kumar Goyal

Amitava Kundu

Sujan Sarathi Ghosh

Method and apparatus for using machine learning to monitor biometric data to provide intelligent alerts are provided. At a first moment in time, first biometric data for a plurality of users are received from a plurality of sensor devices. A group metric is generated by processing the first biometric data using at least one trained machine learning model, and it is determined that the group metric does not satisfy one or more predefined criteria. At a second moment in time, second biometric data for the plurality of users is received from the plurality of sensor devices, and an updated group metric is generated by processing the second biometric data using the at least one trained machine learning model. Upon determining that the updated group metric satisfies the one or more predefined criteria, an indication is provided that the one or more predefined criteria have been satisfied.

Machine learning system for predicting optimal interruptions based on biometric data collected using wearable devices

A computer-implemented method for providing contextual outputs based on varying coordinates related to a target event is provided. The method is implemented by a processor. The processor receives the target event based on a user input and the varying coordinates. The processor then executes a semantic analysis and relationships building operation on the varying coordinates and the target event to generate proposals and provides the contextual outputs based on the proposals. Note that the semantic analysis and relationships building operation reduces recommendation errors by and increases a computing efficiency of the processor with regard to providing the contextual outputs.

Utilizing varying coordinates related to a target event to provide contextual outputs

First information is captured based on monitoring interactions between a user of a communication device and multiple entities. Second information is determined based on monitoring a schedule including upcoming scheduled activities. An incoming call indication and at least a calling phone number related to an incoming call for the communication device are received. Contextual information related to at least the calling phone number and a relevance factor indicating a level of relevance of the incoming call are determined based on the first information and the second information. An indication of the incoming call, the contextual information, and the relevance factor are provided on the communication device.

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Bengaluru, India

Abhijit Singh