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US 2024/0257517 A1Published application
System and method for tagging untagged events
AssigneeVerint Americas Inc.
InventorsMichael Sutton, Zvi Figov, Nir Naor
Life of this patent
Estimating the term…
Abstract
A tagging system gathers all events (tagged and untagged) generated by remote sensors at a location or facility over time. Based on the gathered events the tagging system uses machine learning to train a model to learn the sensor layout of a facility or location and the timing between the triggering of sensors. Once trained, the model can predict the movement and location of individuals and objects throughout the facility based on a starting tagged event. Given a series of tagged and untagged events, the system can use the movement predictions of the model to tag the untagged events in the series with the identification of an individual or object that triggered the generation of the untagged event.
Claims20
A method for tagging untagged events, comprising:
- receiving a first set of tagged events as a first set of tagged data sets and a second set untagged events as a first set of untagged data sets from a set of sensors in a sensor system;
- transmitting the first set of tagged data sets and the first set of untagged data sets from the sensor system to a tagging system;
- generating, by a training preprocessing component, one or more training data sets from the first set of tagged data sets and the first set of untagged data sets;
- training, by a causality modeling component, an event prediction model with the one or more training data sets;
- receiving a second set of tagged events as a second set of tagged data sets and a second set of untagged events as a second set of untagged data sets at a tagging application preprocessing component;
- generating, by the tagging application preprocessing component, one or more data set groupings from the second set of tagged data sets and the second set of untagged data sets;
- applying, by the causality modeling component, the trained event prediction model to each second tagged data set in the data set grouping;
- generating, by the trained event prediction model, one or more predicted events for each second tagged data set in the data set grouping;
- receiving the data set grouping and the one or more predicted events for each second tagged data set at a tagging component;
- comparing, by the tagging component, each predicted event to each second tagged data set received to identify matching predicted events and second tagged data sets;
- and
- tagging one or more second untagged data set by assigning an identification tag associated with the predicted event to the second tagged data set when the second untagged data set and the predicted event are identified as matching.
9 more elements
A system for tagging untagged events, comprising:
- a memory comprising computer readable instructions;
- a processor configured to read the computer readable instructions that when executed causes the system to:
- receive a first set of tagged events as a first set of tagged data sets and a second set untagged events as a first set of untagged data sets from a set of sensors in a sensor system;
- transmit the first set of tagged data sets and the first set of untagged data sets from the sensor system to a tagging system;
- generate, by a training preprocessing component, one or more training data sets from the first set of tagged data sets and the first set of untagged data sets;
- train, by a causality modeling component, an event prediction model with the one or more training data sets;
- receive a second set of tagged events as a second set of tagged data sets and a second set of untagged events as a second set of untagged data sets at a tagging application preprocessing component;
- generate, by the tagging application preprocessing component, one or more data set groupings from the second set of tagged data sets and the second set of untagged data sets;
- apply, by the causality modeling component, the trained event prediction model to each second tagged data set in the data set grouping;
- generate, by the trained event prediction model, one or more predicted events for each second tagged data set in the data set grouping;
- receive the data set grouping and the one or more predicted events for each second tagged data set at a tagging component;
- compare, by the tagging component, each predicted event to each second tagged data set received to identify matching predicted events and second tagged data sets;
- and
- tag one or more second untagged data set by assigning an identification tag associated with the predicted event to the second tagged data set when the second untagged data set and the predicted event are identified as matching.
11 more elements
A non-transitory computer readable medium comprising computer readable code to tag untagged events on a system that when executed by a processor, causes the system to:
- receive a first set of tagged events as a first set of tagged data sets and a second set untagged events as a first set of untagged data sets from a set of sensors in a sensor system;
- transmit the first set of tagged data sets and the first set of untagged data sets from the sensor system to a tagging system;
- generate, by a training preprocessing component, one or more training data sets from the first set of tagged data sets and the first set of untagged data sets;
- train, by a causality modeling component, an event prediction model with the one or more training data sets;
- receive a second set of tagged events as a second set of tagged data sets and a second set of untagged events as a second set of untagged data sets at a tagging application preprocessing component;
- generate, by the tagging application preprocessing component, one or more data set groupings from the second set of tagged data sets and the second set of untagged data sets;
- apply, by the causality modeling component, the trained event prediction model to each second tagged data set in the data set grouping;
- generate, by the trained event prediction model, one or more predicted events for each second tagged data set in the data set grouping;
- receive the data set grouping and the one or more predicted events for each second tagged data set at a tagging component;
- compare, by the tagging component, each predicted event to each second tagged data set received to identify matching predicted events and second tagged data sets;
- and
- tag one or more second untagged data set by assigning an identification tag associated with the predicted event to the second tagged data set when the second untagged data set and the predicted event are identified as matching.
9 more elements
Dependencies are inferred from the claim text.