Greg Skibiski - New York NY, US Alex (Sandy) Pentland - Lexington MA, US Tony Jebara - New York NY, US Christine Lemke - New York NY, US Markus Loecher - Princeton Junction NJ, US Girish Rao - New York NY, US Jason Uechi - Montclair NJ, US Blake Shaw - New York NY, US Joseph Mattiello - New York NY, US David Rosenberg - Scotch Plains NJ, US
Assignee:
Sense Networks, Inc. - New York NY
International Classification:
G06F 17/00 G06N 7/00
US Classification:
706 55
Abstract:
Systems and computer-implemented methods are provided for comparing, associating and deriving associations between two or more spatial temporal data trails. One or more spatial-temporal data trails comprising one or more places are received at a processor. Each place is identified by a spatial temporal data point. And each spatial-temporal data trail is associated with an individual. The similarity between pairs of places is determined to establish one or more groups of places or one or more groups of individuals. Similarity and/groups can be determined based on demographics associated with the place or individual.
Greg Skibiski - New York NY, US Alex (Sandy) Pentland - Lexington MA, US Tony Jebara - New York NY, US Christine Lemke - New York NY, US Markus Loecher - Princeton Junction NJ, US Girish Rao - New York NY, US Jason Uechi - Montclair NJ, US Blake Shaw - New York NY, US Joseph Mattiello - New York NY, US David Rosenberg - Scotch Plains NJ, US
Assignee:
Sense Networks, Inc. - New York NY
International Classification:
G06F 11/00
US Classification:
702188
Abstract:
A method of detecting an event anomaly includes receiving one or more data points, in which each data point represents a spatial or temporal event; associating a unique identifier with each of the one or more data points to obtain one or more individualized data points; distributing the one or more individualized data points across a grid, in which the grid includes one or more cells; determining an event likelihood ratio for one or more of the grid cells; identifying one or more event clusters, in which each event cluster includes one or more of the grid cells; and storing in a data repository an event cluster having a significance level above a threshold significance level.
System And Method Of Performing Location Analytics
Greg Skibiski - New York NY, US Alex (Sandy) Pentland - Lexington MA, US Tony Jebara - New York NY, US Christine Lemke - New York NY, US Markus Loecher - Princeton Junction NJ, US Girish Rao - New York NY, US Jason Uechi - Montclair NJ, US Blake Shaw - New York NY, US Joseph Mattiello - New York NY, US
Assignee:
Sense Networks, Inc. - New York NY
International Classification:
G06F 17/30
US Classification:
707103 R, 707E17045
Abstract:
A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.
System And Method Of Performing Location Analytics
Greg SKIBISKI - New York NY, US Alex (Sandy) PENTLAND - Lexington MA, US Tony JEBARA - New York NY, US Christine LEMKE - New York NY, US Markus LOECHER - Princeton Junction NJ, US Girish RAO - New York NY, US Jason UECHI - Montclair NJ, US Blake SHAW - New York NY, US Joseph MATTIELLO - New York NY, US
Assignee:
Sense Networks, Inc. - New York NY
International Classification:
H04W 4/02
US Classification:
4554563
Abstract:
A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.
System And Method Of Performing Location Analytics
- Glendale CA, US Alex Sandy Pentland - Lexington MA, US Tony Jabara - New York NY, US Christine Lemke - New York NY, US Markus Loecher - Princeton Junction NJ, US Girish Rao - New York NY, US Jason Uechi - Montclair NJ, US Blake Shaw - New York NY, US Joseph Mattiello - New York NY, US
International Classification:
H04W 4/02 G06Q 30/02 G06Q 50/00
Abstract:
A system and method are provided for associating location data from one or more unique sources. The place and time of a unique location enabled device are associated with stored demographic information relating to the particular place and particular time. The place and time of the unique location enabled device are associated with a historical record of past locations and time of locations that the device has been. Based on the association of demographical information and historical information, the unique location enable device is assigned to one or more groups or tribes. The location of all members of the group or tribe can be aggregated and exported for further analysis or display, thereby showing all group or tribe members at a particular time and place.
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Community:
Henry Hank, Virginia Taflinger, Michael Griffet, Bridgette Thompson, Kathy Smith, Michael Bruce, Kathleen Zuvich, Ron Winters, Laurie Massey, Yvonne Kelly, Elizabeth Manley