| CPC G06V 20/44 (2022.01) [G06F 16/7867 (2019.01); G06V 10/774 (2022.01)] | 20 Claims |

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1. 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.
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