Hewlett-Packard Development Company, L.p.

Alexandre Santos Da Silva, Jr

David Murphy

Wagston Staehler

Juliano Vacaro

Thomas Da Silva Paula

Gabriel Rodrigo De Lima Paz

Hiroshi Horii

Jishang Wei

Srikanth Kuthuru

Joao Edwardo Carrion

Jose Dirceu Grundler Ramos

Gabriel Lando

Rafael Dal Zotto

Joao Edurado Carrion

Erika Siegel

Examples are described herein for determining aggregate psychological states of multiple individuals. In various examples, sensor data indicative of affects of multiple individuals may be analyzed. Based on the analyzing, the multiple individuals may be partitioned into multiple distinct clusters of individuals. An aggregate psychological state of the individuals of a given cluster of the multiple distinct clusters of individuals may be determined. Data indicative of the aggregate psychological state may be transmitted to cause a computing device to render output that conveys the aggregate psychological state of the individuals of the cluster.

Conveying aggregate psychological states of multiple individuals

A method includes receiving, with a computing device, a first client request from a first client that identifies a machine learning model and a sensor. The method includes sending, with the computing device, a call to a server to apply the identified machine learning model to a set of data from the identified sensor, in response to the first client request. The method includes receiving, with the computing device, a second client request from a second client that identifies a same machine learning model and sensor as the first client request. The method includes sending, with the computing device, response data from the identified machine learning model to both the first client and the second client without sending an additional call to the server in response to the second client request.

Responding to machine learning requests from multiple clients

A method includes receiving, with a computing device, a configuration file and a client request to apply a machine learning model to a set of data from a sensor. The method includes performing, with the computing device, preprocessing on the set of data from the sensor based on the configuration file to generate preprocessed data. The method includes sending, with the computing device, a call to a model server to apply the machine learning model to the preprocessed data.

Preprocessing sensor data for machine learning

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Porto Alegre, Brazil

Alexandre Santos Da Silva, Jr