Abstract: A user's location may be estimated by applying a probability function to raw user location data taken from various telephony or wireless systems. The probability function may estimate a user's location based on a training dataset that may be generated a priori to the analysis. A training dataset may be generated or updated by analyzing queries made with global positioning system (GPS) data to extract a device's GPS location. The probability function may be generated in part from physical maps. The estimated location may improve location accuracy, especially when attempting to map a user's location with accuracies that may be much smaller than a cell of a cellular telephony system.

Abstract: A traffic routing and analysis system uses data from individual cellular or mobile devices to determine traffic density within a transportation network, such as subways, busses, roads, pedestrian walkways, or other networks. The system may use historical data derived from monitoring people's travel patterns, and may compare historical data to real time or near real time data to detect abnormalities. The system may be used for policy analysis, predicted commute times and route selection based on traffic patterns, as well as broadcast statistics that may be displayed to commuters. The system may be accessed through an application programming interface (API) for various applications, which may include applications that run on mobile devices, desktop or cloud based computers, or other devices.

Abstract: A user's location may be estimated by applying a probability function to raw user location data taken from various telephony or wireless systems. The probability function may estimate a user's location based on a training dataset that may be generated a priori to the analysis. A training dataset may be generated or updated by analyzing queries made with global positioning system (GPS) data to extract a device's GPS location. The probability function may be generated in part from physical maps. The estimated location may improve location accuracy, especially when attempting to map a user's location with accuracies that may be much smaller than a cell of a cellular telephony system.

Abstract: A traffic routing and analysis system uses data from individual cellular or mobile devices to determine traffic density within a transportation network, such as subways, busses, roads, pedestrian walkways, or other networks. The system may use historical data derived from monitoring people's travel patterns, and may compare historical data to real time or near real time data to detect abnormalities. The system may be used for policy analysis, predicted commute times and route selection based on traffic patterns, as well as broadcast statistics that may be displayed to commuters. The system may be accessed through an application programming interface (API) for various applications, which may include applications that run on mobile devices, desktop or cloud based computers, or other devices.

Abstract: A traffic routing and analysis system uses data from individual cellular or mobile devices to determine traffic density within a transportation network, such as subways, busses, roads, pedestrian walkways, or other networks. The system may use historical data derived from monitoring people's travel patterns, and may compare historical data to real time or near real time data to detect abnormalities. The system may be used for policy analysis, predicted commute times and route selection based on traffic patterns, as well as broadcast statistics that may be displayed to commuters. The system may be accessed through an application programming interface (API) for various applications, which may include applications that run on mobile devices, desktop or cloud based computers, or other devices.

Abstract: A traffic routing and analysis system uses data from individual cellular or mobile devices to determine traffic density within a transportation network, such as subways, busses, roads, pedestrian walkways, or other networks. The system may use historical data derived from monitoring people's travel patterns, and may compare historical data to real time or near real time data to detect abnormalities. The system may be used for policy analysis, predicted commute times and route selection based on traffic patterns, as well as broadcast statistics that may be displayed to commuters. The system may be accessed through an application programming interface (API) for various applications, which may include applications that run on mobile devices, desktop or cloud based computers, or other devices.