Abstract: Methods and systems are described for benchmarking a data connection based on congestion control. In one embodiment, a request is received by a first device to perform a performance test of a first data connection between the first device and a second device. The first device transmits, via the first data connection and to the second device, test data according to a congestion window. The first device receives feedback based on at least a portion of the transmitted test data, and determines a bandwidth or data transfer rate of the first data connection based on the feedback and on the congestion window. The first device transmits, over a second data connection, the bandwidth or data transfer rate to the second device for presentation by the device.

Abstract: Methods and systems are described for predicting user (client or customer) sentiment associated with internet speed tests. In one embodiment, a system receives internet speed test data of an internet speed test performed on a data connection between a client device and a remote server. The system determines whether there is a user-provided sentiment score associated with the internet speed test data, and in response to determining that there isn't the user-provided sentiment score, produces, using the internet speed test data as input into a machine learning (ML) model, a predicted user-sentiment score as output of the ML model, wherein the predicted user-sentiment score relates to overall sentiment of a user of the client device with respect to the internet speed test data.

Abstract: Disclosed are methods of generating a visual representation of a wireless service conditions in a three-dimensional display comprising: capturing, from a wireless device, a collection of data comprising wireless service conditions; determining from the data, a latitude and longitude and determining a reference altitude based on said latitude and longitude; determining from the data, a reported altitude in a coordinate system of choice; subtracting the reference altitude from the reported altitude in the coordinate system of choice; determining an estimated above-ground elevation of the data; and displaying in a visual representation the wireless service condition within a three-dimensional graphical image.

Abstract: Methods of creating an indoor confidence level comprising: receiving a location and location accuracy value from or for a device, wherein the location accuracy value is equated to a location accuracy circle; comparing the location and location accuracy circle to a map of known buildings and outdoor locations; and defining an indoor confidence level based upon the percent of overlap of the accuracy radius to a building on said map; and methods of defining an optimization priority among a set of collected data points for network connectivity.

Abstract: Methods of creating an indoor confidence level comprising: receiving a location and location accuracy value from or for a device, wherein the location accuracy value is equated to a location accuracy circle; comparing the location and location accuracy circle to a map of known buildings and outdoor locations; and defining an indoor confidence level based upon the percent of overlap of the accuracy radius to a building on said map; and methods of defining an optimization priority among a set of collected data points for network connectivity.

Abstract: A method of estimating the position of a wireless transmitter comprising: collecting a plurality of wireless measurements between a transmitter and a receiver; drawing a buffer circle around each measurement, having a radius defined by the timing advance delay measurements; plotting a plurality of buffer circles and identifying intersection points for adjacent measurements only; estimating the position based on the intersection of delay measurements from said plurality of wireless measurements.

Abstract: Methods of creating an indoor confidence level comprising: receiving a location and location accuracy value from or for a device, wherein the location accuracy value is equated to a location accuracy circle; comparing the location and location accuracy circle to a map of known buildings and outdoor locations; and defining an indoor confidence level based upon the percent of overlap of the accuracy radius to a building on said map; and methods of defining an optimization priority among a set of collected data points for network connectivity.