Ruth P Willis

US Patent:

7120620, Oct 10, 2006

Filed:

Apr 4, 2005

Appl. No.:

11/098351

Inventors:

Mark E. Dumas - Vienna VA, US
Ruth P. Willis - Alexandria VA, US
Larry E Willis - Alexandria VA, US

Assignee:

Spatial Data Analytics Corporation - Vienna VA

International Classification:

G06F 17/00
G06N 7/00
G06N 7/08

US Classification:

706 58, 706 46, 706 14, 706 45

Abstract:

A forecasting engine and method assists in forecasting occurrences of identifiable events and/or threats based on signature and/or pattern matching. The present invention derives signature for event-types based on a comparison of actual event data with pre-established representational surfaces. The surfaces represent proximity measurements and analysis associated with elements of the geospatial boundary being considered. The measurements and analysis can consider a vast array of potential variables of interest in order to provide a comprehensive, robust forecasting engine. In one embodiment, the present invention considers past data associated with several event-types in order to arrive at an assessment.

US Patent:

20100036793, Feb 11, 2010

Filed:

Jul 20, 2009

Appl. No.:

12/505972

Inventors:

Ruth P. Willis - Alexandria VA, US
Gregory S. Schmidt - Laurel MD, US
Jason Goffeney - Alexandria VA, US

International Classification:

G06N 5/02

US Classification:

706 52, 706 58

Abstract:

A system and method for geospatial forecasting of events that incorporates data error and uncertainty can be provided. The geospatial forecasting system can include a boundary module that is configured to define a geospatial boundary. A layer information and event information module can be provided that is configured to store layer information and event information related to the geospatial boundary. The event information can include location, or position, data about an event. Furthermore, a layer information and event information uncertainty module can be provided that is configured to incorporate data error into the layer information and event information. Finally, a geospatial forecasting module can be configured to receive the layer information and event information with the incorporated data error and process the layer information and event information to determine one or more future events.