Abstract: An interactive telematics system that identifies one or more optimum routes for a user by identifying a plurality of potential routes from a departure location to a destination, calculating attributes of each of the potential routes, comparing the attributes of each of the potential routes to user preferences in a user profile associated with the user, identifying one or more optimized routes for the user by selecting one or more of the potential routes based on the comparison of the attributes of each of the potential routes to the user preferences associated with the user, and outputting the one or more optimized routes to a communications network for transmittal to a remote device associated with the user.

Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Abstract: Satellite images from vast historical archives are analyzed to predict severe storms. We extract and summarize important visual storm evidence from satellite image sequences in a way similar to how meteorologists interpret these images. The method extracts and fits local cloud motions from image sequences to model the storm-related cloud patches. Image data of an entire year are adopted to train the model. The historical storm reports since the year 2000 are used as the ground-truth and statistical priors in the modeling process. Experiments demonstrate the usefulness and potential of the algorithm for producing improved storm forecasts. A preferred method applies cloud motion estimation in image sequences. This aspect of the invention is important because it extracts and models certain patterns of cloud motion, in addition to capturing the cloud displacement.

Abstract: A system and method are disclosed for forecasting probability of precipitation values and most probable precipitation amount values for, preferably, three hour time period increments starting from the present hour through approximately hour 96 (i.e., four days) or beyond. The values are recalculated at the beginning of each hour, based upon existing forecasting information and meteorological data. The values are communicated to end users through a communications channel such as the Internet.

Abstract: A method, system, and software for calculating a multi factor temperature index includes determining the values of at least two weather related parameters. The multi factor temperature index is calculated using the calculated values of the two weather related parameters and an actual temperature value. The two weather related parameters are selected from a group consisting of a wind speed parameter, a solar intensity parameter, a dew point parameter, an atmospheric pressure parameter and a precipitation parameter.

Abstract: A method for conveying both a risk and the degree of risk of a severe weather at a particular geographic location is disclosed. The method involves receiving a location of interest from a requestor, forecasting a risk of severe weather for a specific time period associated with the location, computing a degree of severity level of the risk of severe weather for the location, and generating a report containing the risk forecast and the computed severity level that can be delivered or provided to the requestor. The severity level of the risk of severe weather is provided in an easy to understand graphic or other format.

Abstract: A method, system, and software for calculating a multi factor temperature index includes determining the values of at least two weather related parameters. The multi factor temperature index is calculated using the calculated values of the two weather related parameters and an actual temperature value. The two weather related parameters are selected from a group consisting of a wind speed parameter, a solar intensity parameter, a dew point parameter, an atmospheric pressure parameter and a precipitation parameter.

Abstract: A method, system, and software for calculating a multi factor temperature index includes determining the values of at least two weather related parameters. The multi factor temperature index is calculated using the calculated values of the two weather related parameters and an actual temperature value. The two weather related parameters are selected from a group consisting of a wind speed parameter, a solar intensity parameter, a dew point parameter, an atomospheric pressure parameter and a precipitation parameter.

Abstract: A method, system, and software for calculating a multi factor temperature index includes determining the values of at least two weather related parameters. The multi factor temperature index is calculated using the calculated values of the two weather related parameters and an actual temperature value. The two weather related parameters are selected from a group consisting of a wind speed parameter, a solar intensity parameter, a dew point parameter, an atmospheric pressure parameter and a precipitation parameter.

Abstract: A system and method are disclosed for forecasting probability of precipitation values and most probable precipitation amount values for, preferably, three hour time period increments starting from the present hour through approximately hour 96 (i.e., four days) or beyond. The values are recalculated at the beginning of each hour, based upon existing forecasting information and meteorological data. The values are communicated to end users through a communications channel such as the Internet.