Cisco Technology, Inc.

Huy Phuong Tran

Santosh Ghanshyam Pandey

Abhishek Mukherji

Rong Peng

Abhishek Bhattacharyya

Matthew Aaron Silverman

Xu Zhang

Hugo Latapie

Enzo Fenoglio

David A Maluf

Paul Anthony Polakos

Sivadeep Reddy Kalavakuru

Preethi Natarajan

Vinay S Raghuram

Rahul Dasgupta

Oscar Bejarano Chavez

Avinash Kalyanaraman

Jacob Earl Fussell

Oscar Berjarano Chavez

Xiaohua Fang

Edmund Cameron Duhaime

Correcting for antennae spatial distortions in Radio Frequency (RF) localization may be provided. A plurality of actual locations associated with a plurality of Access Point (APs) may be received. Then a plurality of signal strengths associated with the plurality of APs may be received. Based on the plurality of signal strengths, a model may be created that models a plurality of inference errors respectively corresponding to the plurality of APs between a plurality of inferred locations respectively corresponding to the plurality of APs and the plurality of actual locations. The model may then be used in determining a location of a device.

Correcting for antennae spatial distortions in radio frequency (RF) localizations

Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.

Partial phase vectors as network sensors

Various embodiments herein disclose improving battery life while determining a location of a Bluetooth device. A corresponding method comprises receiving an identifier for a Bluetooth Low Energy (BLE) device to locate in an environment comprising a plurality of access points (APs). The method further comprises identifying a first AP of the plurality of APs communicating with the BLE device at a first power level. The method also comprises instructing, using the first AP, the BLE device to increase a transmission power level of the BLE device until a threshold number of APs of the plurality of APs, including the first AP, receive communications from the BLE device. The method additionally comprises receiving an RSSI value from each of the threshold number of APs based on the communications from the BLE device. The method also comprises computing a location of the BLE device in the environment based on the RSSI values.

Conserving battery life during Bluetooth device localization

An access point includes first and second radios that operate in accordance with first and second wireless protocols, respectively. The access point performs a method including receiving a first protocol packet of the first wireless protocol and a second protocol packet of the second wireless protocol transmitted by a wireless device over a communication channel, and measuring a first received power of the first protocol packet and a second received power of the second protocol packet at the access point. The method further includes determining whether reception times of the first protocol packet and the second protocol packet are within a coherence time for the communication channel and, when the reception times are within the coherence time, combining the first received power and the second received power into a multiprotocol received power. The method also includes determining a location of the wireless device based on the multiprotocol received power.

Multi-protocol concurrent RSSI and AoA for location computation

In one embodiment, a service obtains spatial information regarding a physical area. The service estimates locations of a device within the physical area over time, based on wireless signals sent by the device. The service generates a set of images based on the spatial information regarding the physical area and on the estimated locations of the device within the physical area over time. The service updates an estimated location of the device by inputting the generated set of images to a machine learning model trained to minimize a location estimation error.

Image-based framework for improving location estimate accuracy in indoor positioning systems

An enterprise system configures access point devices at an enterprise location to communicate with a location determination system. The location determination system receives wireless signal attributes of user computing devices broadcasting Wi-Fi signal data at the enterprise location from one or more access point devices. For a particular time window, the location determination system determines aggregated features of received wireless signal data across all access point devices, and classifies each of the user computing devices as moving or stationary by applying the wireless signal data to a model. For each of the user computing devices determined to be moving, the location determination system calculates a respective position of the user computing device based on the wireless signal data. For each of the user computing devices determined to be stationary, the location determination system does not calculate a respective position of the respective user computing device.

Motion detection for passive indoor positioning system

A plurality of access points located within a building structure may provide various location-based services, such as navigation, to mobile devices within the building structure. To more accurately determine the location of the plurality of access points, a floorplan of the interior of the building structure may be obtained. A plurality of images of the interior of the building structure is then obtained. At least one of the images includes an image of at least one of the plurality of access points. A plurality of reference points may also be located within the building structure and obtained. Based on the plurality of images, reference points, and the floorplan, a composite image of the interior of the structure is generated. Based on the composite image, the location of each of the plurality of access points is determined.

Precise access point placement and location measurement

It may be determined that each of a first plurality of devices was stationary at a location based on received first location information. Next, a first estimated ground truth may be determined for each of the first plurality of devices at the location based on the first location information corresponding to each of the respective first plurality of devices at the location. A first plurality of location estimation errors may then be determined for each of the first plurality of devices at the location respectively based on the first location information corresponding to each of the respective first plurality of devices at the location and the first estimated ground truth for each of the respective first plurality of devices at the location. Next, each of the determined first plurality of location estimation errors for each of the first plurality of devices at the location may be aggregated to provide a first location accuracy measurement for the location.

Benchmarking and measurement of location accuracy using crowdsourced data

A method including obtaining location estimates of a wireless mobile device inside a structure based on wireless signals transmitted by the wireless mobile device and received at a plurality of wireless access points, wherein the inside of the structure is represented by a plurality of path segments; modeling a transition from a first estimated location of the wireless mobile device to a second estimated location of the wireless mobile device by minimizing a ratio of an angle to a length between the first estimated location and the second estimated location; selecting, based on the modeling a particular path segment of the plurality of path segments; and aligning the second estimated location of the mobile device to the particular path segment. An apparatus and a computer-readable storage media implementing the method are also disclosed.

Path segment matching for wireless indoor location applications

An efficient process is provided that exploits features in historical and current client location data to forecast client counts of different zones up to several hours ahead. These features may be obtained from correlations of client counts of multiple zones in a recent and long period of time. These features may also be combined using techniques that choose the best performing method for a particular dataset and a particular lookahead time. This process provides better forecast/prediction on the zone-based client count data, and is very useful in customer analytics which can now show the future predicted value. This can help the analytics customers to plan their operations based on the location analytics.

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Portland, OR, United States of America

Huy Phuong Tran