Abstract: Characterizing traffic conditions by analyzing operational data taken from a wireless communication network to generate traffic information. Location estimates can be made based on processing the operational data. This location can be combined with computerized street maps to measure the time it takes to get from one geographic area to another. By aggregating and analyzing anonymous data from thousands of devices, the present invention is able to determine real-time and historical travel times and velocities between cities, intersections and along specific routes.

Abstract: Characterizing traffic conditions by analyzing operational data taken from a wireless communication network to generate traffic information. Location estimates can be made based on processing the operational data. This location can be combined with computerized street maps to measure the time it takes to get from one geographic area to another. By aggregating and analyzing anonymous data from thousands of devices, the present invention is able to determine real-time and historical travel times and velocities between cities, intersections and along specific routes.

Abstract: A method and system for computing a performance forecast for an e-business system or other computer architecture to proactively manage the system to prevent system failure or slow response time. The system is adapted to obtain measured input values from a plurality of internal data sources and external data sources to predict a system's performance especially under unpredictable and dramatically changing traffic levels in an effort to proactively manage the system to avert system malfunction or slowdown. The performance forecasting system can include both intrinsic and extrinsic variables as predictive inputs. Intrinsic variables include measurements of the systems own performance, such as component activity levels and system response time. Extrinsic variables include other factors, such as the time and date, whether an advertising campaign is underway, and other demographic factors that may effect or coincide with increased network traffic.

Abstract: Providing traffic information by using operational data developed by a wireless communication network to generate traffic information. Location information from the network can be combined with computerized street maps to measure the time it takes to get from one geographic area to another. By aggregating and analyzing anonymous data from thousands of devices, the present invention is able to determine real-time and historical travel times and velocities between cities, intersections and along specific routes.

Abstract: A “Rapid Learner Client Service” (RLCS) system that allows a large number of end-users to obtain the benefits of a sophisticated neural-network forecasting system. Rather than purchasing or developing a forecasting system of their own, RLCS clients subscribe to a forecasting service performed by forecasting equipment located at a remote site. This allows a single highly sophisticated forecasting system to meet the forecasting needs of a large number of subscribers. This forecasting service is performed by an RLCS server that periodically and automatically accesses the subscriber's computer to obtain a fresh set of input data. Alternatively, the subscriber's computer may contact the RLCS server to initiate the process. This input data is then downloaded to the RLCS server, where it is checked and corrected for errors by imputing values for missing or deviant input values.

Abstract: Providing traffic information by using operational data developed by a wireless communication network to generate traffic information. Location information from the network can be combined with computerized street maps to measure the time it takes to get from one geographic area to another. By aggregating and analyzing anonymous data from thousands of devices, the present invention is able to determine real-time and historical travel times and velocities between cities, intersections and along specific routes.

Abstract: A method and system for computing a performance forecast for an e-business system or other computer architecture to proactively manage the system to prevent system failure or slow response time. The system is adapted to obtain measured input values from a plurality of internal data sources and external data sources to predict a system's performance especially under unpredictable and dramatically changing traffic levels in an effort to proactively manage the system to avert system malfunction or slowdown. The performance forecasting system can include both intrinsic and extrinsic variables as predictive inputs. Intrinsic variables include measurements of the systems own performance, such as component activity levels and system response time. Extrinsic variables include other factors, such as the time and date, whether an advertising campaign is underway, and other demographic factors that may effect or coincide with increased network traffic.