The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 25, 2021

Filed:

Sep. 14, 2017
Applicant:

Foursquare Labs, Inc., New York, NY (US);

Inventors:

Stephanie Yang, New York, NY (US);

Lauren Hannah, Millburn, NJ (US);

Daniel Kronovet, New York, NY (US);

Catgatay Berk Kapicioglu, New York, NY (US);

Assignee:

Foursquare Labs, Inc., New York, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/20 (2019.01); G06N 20/00 (2019.01); G06F 16/29 (2019.01); H04W 4/021 (2018.01); H04W 4/38 (2018.01); G06N 7/00 (2006.01); G06Q 30/02 (2012.01);
U.S. Cl.
CPC ...
G06N 20/20 (2019.01); G06F 16/29 (2019.01); G06N 20/00 (2019.01); H04W 4/021 (2013.01); G06N 7/005 (2013.01); G06Q 30/0201 (2013.01); H04W 4/38 (2018.02); Y02D 30/70 (2020.08);
Abstract

This disclosure relates to systems and methods for passive visit detection. In aspects, a mobile device comprising a set of sensors may collect and store sensor data from the set of sensors in response to detecting a movement event or user interaction data. The collected sensor data may be processed and provided as input to one or more predictive or statistical models. The model(s) may evaluate the sensor data to detect mobile device location, movement events and visit events. The model(s) may also be used to determine correlations between features of the sensor data and movement- or location-based events, optimize the types of data collected by the set of sensors, extend localized predictions to large-scale ecosystems, and generate battery-efficient state predictions. In aspects, the model(s) may be trained using labeled and/or unlabeled data sets of sensor data.


Find Patent Forward Citations

Loading…