Continuous time alignment of a collection of independent sensors
AssigneeInternational Business Machines Corporation
InventorsAvner ABRAMI, Stephen J. HEISIG
Life of this patent
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Abstract
Embodiments for continuous time alignment of a collection of independent sensors monitoring a common entity by one or more processors. One or more activity events associated with a monitored entity may be identified in the time series sensor data collected from a plurality of sensors. The one or more activity events may be dynamically characterized in the time series sensor data using a machine learning operation. The time series data streams from each of the plurality of sensors may be time-aligned by aligning the one or more activity events.
Claims20
A method for continuous time alignment of time series data from a collection of independent sensors by one or more processors, comprising:
- identifying one or more activity events, associated with a monitored entity, in the time series sensor data collected from a plurality of sensors;
- dynamically characterizing the one or more activity events in the time series sensor data using a machine learning operation;
- and
- time-aligning time series data streams from each of the plurality of sensors by aligning the one or more activity events.
A system for continuous time alignment of time series data from a collection of independent sensors, comprising:
- one or more computers with executable instructions that when executed cause the system to:
- identify one or more activity events, associated with a monitored entity, in the time series sensor data collected from a plurality of sensors;
- dynamically characterize the one or more activity events in the time series sensor data using a machine learning operation;
- and
- time-align time series data streams from each of the plurality of sensors by aligning the one or more activity events.
A computer program product for continuous time alignment by one or more processors, the computer program product comprising a non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:
- an executable portion that identifies one or more activity events, associated with a monitored entity, in the time series sensor data collected from a plurality of sensors;
- an executable portion that dynamically characterizes the one or more activity events in the time series sensor data using a machine learning operation;
- and
- an executable portion that time-aligns time series data streams from each of the plurality of sensors by aligning the one or more activity events.
Dependencies are inferred from the claim text.