Microsoft Technology Licensing, LLC

LaSean Tee Smith

Kenneth Liam Kiemele

John Benjamin Hesketh

Evan Lewis Jones

Donna Katherine Long

Bryant Daniel Hawthorne

Jamie R Cabaccang

Priya Ganadas

Jennifer Jean Choi

James Lewis Nance

Techniques for generating a machine learning model to detect event instances from physical sensor data, including applying a first machine learning model to first sensor data from a first physical sensor at a location to detect an event instance, determining that a performance metric for use of the first machine learning model is not within an expected parameter, obtaining second sensor data from a second physical sensor during a period of time at the same location as the first physical sensor, obtaining third sensor data from the first physical sensor during the period of time, generating location-specific training data by selecting portions of the third sensor data based on training event instances detected using the second sensor data, training a second ML model using the location-specific training data, and applying the second ML model instead of the first ML model for detecting event instances.

Automated localized machine learning training

A computer system is provided that includes a server configured to store a plurality of location accounts, each location account being associated with a physical space at a recorded geospatial location. The plurality of location accounts utilize shared data definitions of a physical space parameter. Each physical space is equipped with a corresponding on-premise sensor configured to detect measured values for the physical space parameter over time and send to the server a data stream indicating the measured values. The computer system further includes a network portal, via which an authorized user for a location account can selectively choose whether to share the measured values or a summary thereof with other location accounts via the network portal.

Sharing measured values of physical space parameters

A device for removal of personally identifiable data receives monitoring data acquired by a sensor. The monitoring data including personally identifiable data relating to one or more individuals being monitored. The system processes the acquired monitoring data to remove the personally identifiable data by at least one of abstraction or redaction while the monitoring data is located on the device. The processed monitoring data having the personally identifiable data removed can thereby be transmitted external to the device with reduced security risk.

Removing personally identifiable data before transmission from a device

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Bellevue, WA, United States of America

LaSean Tee Smith