Samsung Electronics Co., Ltd.

Synopsys, Inc.

Apple Inc.

Jasvinder Singh

Dhiraj Goswami

Ngai Ngai William Hung

David Benjamin Millman

Koichi Mori

Qiang Qiang

Darin Tay

Guillermo R Maturana

Shalinder Singh Sidhu

Yifei Jiang

Anders M Holtsberg

Danny R Bennett

Satheesh Sudarsan

Yannick Pellet

Simon J Gibbs

Jun Yang

Jahshan A Bhatti

Brian Stephen Smith

Anthony S Liot

Bulent Kasman

Benjamin A Detwiler

Muralidhar Kattimani

Jason Robert Wither

Wuzhou Zhang

Dongfang Zheng

A method comprising: receiving a radio map of an indoor venue using survey data collected by a survey device positioned throughout the venue, the radio map including a boundary; receiving harvest data from a mobile device, wherein at least some of the harvest data are obtained by the mobile device while the mobile device is positioned at locations that are outside of the boundary; determining, based on the harvest data, a trajectory of the mobile device, wherein at least some of the trajectory resides outside of the boundary; identifying one or more locations on or proximate to the trajectory; and extending the radio map using the survey data and the one or more identified locations, wherein the extended radio map is defined at least in part by an extension of the boundary to encompass the one or more identified locations.

Extending a radio map

Embodiments are disclosed for compressing radio maps of fingerprint-based positioning systems using different compression models. In an embodiment, a method comprises: receiving, by a computing device, access point (AP) data from a plurality of mobile devices operating in a geographic region, the AP data including signal strength measurements of AP signals received at a plurality of reference locations in the geographic region and uncertainty measurements associated with the signal strength measurements; determining a level of accuracy with the first compression model; responsive to the determining, selecting one of the first compression model or a second compression model to compress the AP data, the second compression model being different than the first compression model; compressing the AP data using the selected compression model; and responsive to a request from a mobile device operating in the geographic region, sending a data packet including the compressed AP data to the mobile device.

Compressing radio maps using different compression models

A method, mobile device, and non-transitory computer readable medium for transmitting information. The method includes determining, by a mobile device, a distance between the mobile device and another device in response to a request for the mobile device to transmit the information. The method also includes determining, by the mobile device, whether the distance between the mobile device and the other device is within a threshold distance. Additionally, the method includes transmitting, by the mobile device, the information to the other device after determining that the distance between the mobile device and the other device is within the threshold distance.

Method and apparatus to trigger mobile payment based on distance

In one aspect, a method for determining a location of a landmark using a map is described. Trajectory data is obtained indicating movement of a device at an area. The trajectory data indicates a landmark. A map is obtained of the area. At least a portion of the trajectory data is compared and/or matched with at least a portion of the map. Based on the matching, a location of the landmark is determined in the map. Various implementations involve system, devices and software relating to the above method.

Landmark location determination

Methods and apparatuses are described for assigning random values to a set of random variables so that the assigned random values satisfy a set of constraints. A constraint solver can receive a set of constraints that is expected to cause performance problems when the system assigns random values to the set of random variables in a manner that satisfies the set of constraints. For example, modulo constraints and bit-slice constraints can cause the system to perform excessive backtracking when the system attempts to assign random values to the set of random variables in a manner that satisfies the set of constraints. The system can rewrite the set of constraints to obtain a new set of constraints that is expected to reduce and/or avoid the performance problems. The system can then assign random values to the set of random variables based on the new set of constraints.

Optimizing constraint solving by rewriting at least one bit-slice constraint

A rule set is used to generate an indoor map of a building from partial map data. In one embodiment, the partial map data is based at least in part on crowd sourced trajectory data. In one embodiment, a probabilistic rule set describes relationships in space usage of the indoor building. Hypothesis testing is performed. A most likely complete layout is determined, based on the partial coverage data and the rule set, which preserves the partial map data.

Rule based completion of maps with partial data

Embodiments are disclosed for compressing radio maps of fingerprint-based positioning systems. In an embodiment, a method comprises: receiving access point (AP) data from a plurality of mobile devices operating in a geographic region, the AP data including signal strength measurements of AP signals received at a plurality of reference locations in the geographic region; filtering the AP data to remove outlier AP data; fitting a surface to the AP data; projecting AP data at surface control points onto a two-dimensional image grid; determining a boundary surrounding locations of the AP data at the surface control points; encoding the boundary; encoding the AP data at the surface control points included within the boundary; generating compressed radio maps from the encoded AP data; and responsive to a request from a mobile device operating in the geographic region, sending a data packet including the compressed radio maps to the mobile device.

Compressing radio maps

Mapping through crowdsourcing includes determining, using a processor, segments for a plurality of trajectories, wherein each trajectory includes radio frequency (RF) data from a communication device, determining, using the processor, RF features for the segments, and forming, using the processor, clusters of the segments according to the RF features. One or more routes of a map are generated from the clusters using the processor.

Location determination, mapping, and data management through crowdsourcing

Optimizing constraint solving by rewriting at least one modulo constraint

Some embodiments provide systems and techniques to facilitate construction of a canonical representation (CR) which represents a logical combination of a set of logical functions. During operation, the system can receive a CR-size limit. Next, the system can construct a set of CRs based on the set of logical functions, wherein each CR in the set of CRs represents a logical function in the set of logical functions. The system can then combine a subset of the set of CRs to obtain a combined CR. Next, the system can identify a problematic CR which when combined with the combined CR causes the CR-size limit to be exceeded. The system can then report the problematic CR and/or a logical function associated with the problematic CR to a user, thereby helping the user to identify an error in the set of logical functions.

Method and apparatus for constructing a canonical representation

Some embodiments provide a system for adaptively performing state-to-symbolic transformation in a canonical representation which is used for generating random stimulus for a constrained-random simulation. The system can construct a canonical representation for a set of constraints using the set of random variables and the subset of the state variables in the constraints. Next, the system can use the canonical representation to generate random stimulus for the constrained-random simulation, and monitor parameters associated with the constrained-random simulation. Next, the system can add state variables to or remove state variables from the canonical representation based at least on the monitored parameters. The system can then use the modified canonical representation which has a different set of state variables to generate random stimulus for the constrained-random simulation.

Growing community of inventors

Santa Clara, CA, United States of America

Jasvinder Singh