公开(公告)号：US08665154B2

公开(公告)日：2014-03-04

申请号：US13106874

申请日：2011-05-13

Applicant: Jyh-Han Lin ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Pradipta Kumar Basu

IPC: G01S3/02

CPC classification number: G01S5/0252

Abstract: Embodiments order observed beacons based on relative signal strength to create a correspondence between beacon sets and positions. A computing device such as a mobile device provides a positioned observation including a plurality of observed beacons and a position of the mobile device during observation. The observed beacons are ordered based on quality indicators such as signal strength relative to each other. A set of the beacons are selected based on the ordering (e.g., the beacons with the strongest signal strength are selected in order). The position of the observing mobile device is associated with the beacon set to enable location inference for other devices providing observations including the same beacon set.

Abstract translation: 实施例基于相对信号强度的观察信标，以产生信标集和位置之间的对应关系。 诸如移动设备的计算设备在观察期间提供包括多个观察到的信标的定位观察和移动设备的位置。 观察到的信标是基于诸如信号强度相对于彼此的质量指标来排序的。 基于排序来选择一组信标（例如，按顺序选择具有最强信号强度的信标）。 观察移动设备的位置与信标集合相关联，以便为提供包括相同信标集的观察的其他设备启用位置推断。

公开(公告)号：US08577389B2

公开(公告)日：2013-11-05

申请号：US13185520

申请日：2011-07-19

Applicant: Jyh-Han Lin ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

IPC: H04W68/00

CPC classification number: H04W64/003 ,  H04W24/10 ,  H04W64/00

Abstract: Embodiments analyze crowd-sourced data to identify a moved or moving beacon. The crowd-sourced data involving a particular beacon is filtered based on a cluster start time associated with the beacon. A clustering analysis groups the filtered crowd-sourced data for the beacon into a plurality of clusters based on spatial distance. Timestamps associated with the crowd-sourced data in the clusters are compared to select one of the clusters. The crowd-sourced data associated with the selected cluster is used to determine position information for the moved beacon. The cluster start time for the beacon is adjusted based on the earliest timestamp associated with the positioned observations corresponding to the selected cluster. Adjusting the cluster start time removes from a subsequent analysis the positioned observations associated with one or more prior positions of the beacon.

公开(公告)号：US08559975B2

公开(公告)日：2013-10-15

申请号：US13252605

申请日：2011-10-04

Applicant: Jyh-Han Lin ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Pradipta Kumar Basu

IPC: H04W24/00

CPC classification number: G01S5/0252 ,  G01S5/021

Abstract: Training datasets and test datasets consisting of observations (i.e., RSS measurements) partitioned per a mapping tile system are used to evaluate possible RSS weighting functions for each such tile. The observations from the training dataset are used to determine an optimal weighting function based on the training dataset that minimizes the error for the test data, wherein the error may be a function of the deltas between GPS positions of observations in the test dataset and predicted positions from the RSS weighted functions applied to test data. The accuracy of the optimal weighted function for each tile is characterized to determine whether to use the weighted function or an alternative (such as a non-weighted function) for subsequent inquiries.

Abstract translation: 训练数据集和测试数据集被用于评估每个这样的瓦片可能的RSS加权函数，每个测绘数据集和测试数据集由每个映射瓦片系统划分的观测（即RSS测量）组成。 训练数据集的观测值用于确定基于最小化测试数据误差的训练数据集的最优加权函数，其中误差可以是测试数据集中观测值的GPS位置与预测位置之间的差值的函数 从RSS加权函数应用于测试数据。 每个瓦片的最佳加权函数的准确性的特征在于确定是否使用加权函数或替代（例如非加权函数）用于随后的查询。

公开(公告)号：US20130023282A1

公开(公告)日：2013-01-24

申请号：US13252605

申请日：2011-10-04

Applicant: Jyh-Han Lin ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Pradipta Kumar Basu

IPC: H04W24/00

CPC classification number: G01S5/0252 ,  G01S5/021

Abstract: Training datasets and test datasets consisting of observations (i.e., RSS measurements) partitioned per a mapping tile system are used to evaluate possible RSS weighting functions for each such tile. The observations from the training dataset are used to determine an optimal weighting function based on the training dataset that minimizes the error for the test data, wherein the error may be a function of the deltas between GPS positions of observations in the test dataset and predicted positions from the RSS weighted functions applied to test data. The accuracy of the optimal weighted function for each tile is characterized to determine whether to use the weighted function or an alternative (such as a non-weighted function) for subsequent inquiries.

Abstract translation: 训练数据集和测试数据集被用于评估每个这样的瓦片可能的RSS加权函数，每个测绘数据集和测试数据集由每个映射瓦片系统划分的观测（即RSS测量）组成。 训练数据集的观测值用于确定基于最小化测试数据误差的训练数据集的最优加权函数，其中误差可以是测试数据集中观测值的GPS位置与预测位置之间的差值的函数 从RSS加权函数应用于测试数据。 每个瓦片的最佳加权函数的准确性的特征在于确定是否使用加权函数或替代（例如非加权函数）用于随后的查询。

公开(公告)号：US20130116965A1

公开(公告)日：2013-05-09

申请号：US13289543

申请日：2011-11-04

Applicant: Jyh-Han Lin ,  Gursharan Singh Sidhu ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Gursharan Singh Sidhu ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

IPC: G06F15/00

CPC classification number: G06F15/00 ,  G01S5/021 ,  G01S5/0252 ,  G01S5/0263 ,  H04W64/00

Abstract: Embodiments respond to a position inference request from a computing device to determine a location of a computing device. The position inference request received from the computing device identifies a set of beacons observed by the computing device. A geographic area is estimated in which the computing device is located using the set of beacons. At least one location method is selected to identify a location of the computing device within the geographic area. In some cases two or more location methods may he employed and their results combined using, for example, a weighting function. The location of the computing device is determined within the geographic area using the set of beacons and the selected location method(s). The location that is determined is communicated to the computing device.

Abstract translation: 实施例响应来自计算设备的位置推断请求以确定计算设备的位置。 从计算设备接收的位置推断请求标识由计算设备观察到的一组信标。 使用一组信标估计计算设备所在的地理区域。 选择至少一个位置方法来识别该地理区域内的计算设备的位置。 在某些情况下，他可以采用两种或多种定位方法，并且使用例如加权函数来组合它们的结果。 使用一组信标和所选择的位置方法在地理区域内确定计算设备的位置。 确定的位置被传送到计算设备。

公开(公告)号：US20120184292A1

公开(公告)日：2012-07-19

申请号：US13185520

申请日：2011-07-19

Applicant: Jyh-Han Lin ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

IPC: H04W24/00

CPC classification number: H04W64/003 ,  H04W24/10 ,  H04W64/00

Abstract: Embodiments analyze crowd-sourced data to identify a moved or moving beacon. The crowd-sourced data involving a particular beacon is filtered based on a cluster start time associated with the beacon. A clustering analysis groups the filtered crowd-sourced data for the beacon into a plurality of clusters based on spatial distance. Timestamps associated with the crowd-sourced data in the clusters are compared to select one of the clusters. The crowd-sourced data associated with the selected cluster is used to determine position information for the moved beacon. The cluster start time for the beacon is adjusted based on the earliest timestamp associated with the positioned observations corresponding to the selected cluster. Adjusting the cluster start time removes from a subsequent analysis the positioned observations associated with one or more prior positions of the beacon.

Abstract translation: 实施例分析人群来源的数据以识别移动或移动的信标。 基于与信标相关联的群集开始时间来过滤涉及特定信标的人群来源的数据。 聚类分析基于空间距离将经滤波的信标源数据分组为多个聚类。 与群集中的人群来源的数据相关联的时间戳进行比较，以选择一个集群。 与所选择的群集相关联的人群来源的数据用于确定移动的信标的位置信息。 基于与所选择的集群对应的定位观察相关联的最早时间戳来调整信标的集群开始时间。 调整群集开始时间从随后的分析中移除与信标的一个或多个先前位置相关联的定位观察。

公开(公告)号：US09507747B2

公开(公告)日：2016-11-29

申请号：US13289543

申请日：2011-11-04

Applicant: Jyh-Han Lin ,  Gursharan Singh Sidhu ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Gursharan Singh Sidhu ,  Sindhura Bandhakavi ,  Pradipta Kumar Basu

IPC: G01S1/00 ,  G06F15/00 ,  G01S5/02 ,  H04W64/00

CPC classification number: G06F15/00 ,  G01S5/021 ,  G01S5/0252 ,  G01S5/0263 ,  H04W64/00

Abstract: Embodiments respond to a position inference request from a computing device to determine a location of a computing device. The position inference request received from the computing device identifies a set of beacons observed by the computing device. A geographic area is estimated in which the computing device is located using the set of beacons. At least one location method is selected to identify a location of the computing device within the geographic area. In some cases two or more location methods may be employed and their results combined using, for example, a weighting function. The location of the computing device is determined within the geographic area using the set of beacons and the selected location method(s). The location that is determined is communicated to the computing device.

Abstract translation: 实施例响应来自计算设备的位置推断请求以确定计算设备的位置。 从计算设备接收的位置推断请求标识由计算设备观察到的一组信标。 使用一组信标估计计算设备所在的地理区域。 选择至少一个位置方法来识别该地理区域内的计算设备的位置。 在一些情况下，可以使用两个或多个位置方法，并且使用例如加权函数将它们的结果组合。 使用一组信标和所选择的位置方法在地理区域内确定计算设备的位置。 确定的位置被传送到计算设备。

公开(公告)号：US20120286997A1

公开(公告)日：2012-11-15

申请号：US13106874

申请日：2011-05-13

Applicant: Jyh-Han Lin ,  Pradipta Kumar Basu

Inventor： Jyh-Han Lin ,  Pradipta Kumar Basu

IPC: G01S5/02

CPC classification number: G01S5/0252

Abstract: Embodiments order observed beacons based on relative signal strength to create a correspondence between beacon sets and positions. A computing device such as a mobile device provides a positioned observation including a plurality of observed beacons and a position of the mobile device during observation. The observed beacons are ordered based on quality indicators such as signal strength relative to each other. A set of the beacons are selected based on the ordering (e.g., the beacons with the strongest signal strength are selected in order). The position of the observing mobile device is associated with the beacon set to enable location inference for other devices providing observations including the same beacon set.

Abstract translation: 实施例基于相对信号强度的观察信标，以产生信标集和位置之间的对应关系。 诸如移动设备的计算设备在观察期间提供包括多个观察到的信标的定位观察和移动设备的位置。 观察到的信标是基于诸如信号强度相对于彼此的质量指标来排序的。 基于排序来选择一组信标（例如，按顺序选择具有最强信号强度的信标）。 观察移动设备的位置与信标集合相关联，以便为提供包括相同信标集的观察的其他设备启用位置推断。

公开(公告)号：US08990411B2

公开(公告)日：2015-03-24

申请号：US12765368

申请日：2010-04-22

Applicant: Joel Robert Bergman ,  Jyh-Han Lin ,  Fadi Al Sayed Hassan ,  Pavani Haridasyam ,  Ryan Bane

Inventor： Joel Robert Bergman ,  Jyh-Han Lin ,  Fadi Al Sayed Hassan ,  Pavani Haridasyam ,  Ryan Bane

IPC: G06F15/16 ,  H04W76/04 ,  H04L12/707 ,  H04L12/703

CPC classification number: H04W76/041 ,  H04L45/22 ,  H04L45/28 ,  H04W76/22

Abstract: Dynamically evaluating candidate connections as alternatives to an active connection between a first computing device and a second computing device. The first computing device transitions to one of the candidate connections to replace the active connection based on the evaluation. The evaluation and transition occurs based on time intervals, events, or conditions. Maintaining the candidate connections enables mobile devices, for example, to be resilient to and tolerant of topology changes affecting the active connection.

Abstract translation: 将候选连接动态地评估为第一计算设备和第二计算设备之间的活动连接的替代。 第一计算设备转换到候选连接之一以基于评估来替换活动连接。 评估和转换基于时间间隔，事件或条件进行。 维护候选连接使得移动设备例如能够抵御和容忍影响活动连接的拓扑变化。

公开(公告)号：US08793031B2

公开(公告)日：2014-07-29

申请号：US13294161

申请日：2011-11-10

Applicant: Anoop Anantha ,  Jyh-Han Lin

Inventor： Anoop Anantha ,  Jyh-Han Lin

IPC: G05B19/02

CPC classification number: G06Q10/10 ,  G06Q30/00 ,  G06Q50/01 ,  G06Q50/30

Abstract: Embodiments enhance the functionality of a vehicle, a user device, or both by the selection and sharing of data. Upon detection of each other, the vehicle device and the user device obtain and share data. The data may be associated with the user, the user computing device, and/or the vehicle and may be stored in cloud-based services. Functionality of the vehicle and/or user device is customized to the user based on the shared data. For example, the user device may provide assisted global positioning system (GPS) data to the vehicle to reduce a time-to-fix (TTF) when determining a location of the vehicle. In other examples, settings of the vehicle are personalized to the user, and location-relevant content is downloaded to the user device.

Abstract translation: 实施例通过选择和共享数据来增强车辆，用户装置或两者的功能。 在检测到彼此之后，车辆装置和用户装置获取和共享数据。 数据可以与用户，用户计算设备和/或车辆相关联，并且可以被存储在基于云的服务中。 基于共享数据，为用户定制车辆和/或用户设备的功能。 例如，用户设备可以向车辆提供辅助的全球定位系统（GPS）数据，以在确定车辆的位置时减少固定时间（TTF）。 在其他示例中，车辆的设置对用户进行个性化，并且将位置相关内容下载到用户设备。