Unisys Corporation

Dmitriy Yarmaliuk

Edward T Cavanagh

Michael C Leap

Brittney Burchett

Michael Di Domenico

Cody Finn

Methods and systems for providing an emergency incident response are described. Data is received from a plurality of heterogeneous data feeds each having a native format and including one or more publically-available data feeds. Event data is extracted from the received data, the event data representing one or more events from one or more of the plurality of heterogeneous data feeds, and the event data is translated from the native format into a standardized analysis format. Further, an existence and a priority level of at least one emergency incident contemporaneous with the event data and based at least in part on the event data is determined, the priority level being selected from among a plurality of predefined priority levels, and a graphical user interface including a message describing the at least one determined emergency incident is displayed.

Emergency incident detection platform

Methods and systems for determining public events are described. Data is received from a plurality of heterogeneous data feeds each having a native format. Event data objects are generated based on the received data, the event data objects each including at least a human readable message, an event time, and an event location. The human readable message of each of the event data objects is parsed into keywords, and the event data objects are grouped into one or more public events based on the keywords, time, location, and a sentiment based on the keywords. The public events are filtered based on a filter score, and the event data objects are clustered based on sentiment, location, and time. A density of the clustered event data objects is determined, and the validity of the public events is determined by a comparison of the density to a predetermined density threshold.

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Malvern, PA, United States of America

Dmitriy Yarmaliuk