Systems and methods of gathering and distributing critical weather event information

    公开(公告)号:US10147326B2

    公开(公告)日:2018-12-04

    申请号:US15443298

    申请日:2017-02-27

    Abstract: A method of gathering and distributing critical weather event information is provided. The method includes monitoring for critical weather events based on defined critical weather event thresholds with an onboard producer weather detection unit of at least one producer vehicle. The critical weather event thresholds are dynamically reconfigured based at least in part on consumption needs of the consumer vehicle. The detected critical weather event and associated time stamp and geolocation information are communicated to a base station. The detected critical weather event is fused with other weather data at the base station to produce a unified weather event image that includes the detected critical weather event. Prediction algorithms are applied to the unified weather event image and are parsed into predefined grid cells of a geo-spatial grid. The predicted weather data is up-linked to a consumer vehicle anticipated to travel within at least one grid cell of the geo-spatial grid.

    Aggregation and distribution of real-time data

    公开(公告)号:US10311740B2

    公开(公告)日:2019-06-04

    申请号:US15194263

    申请日:2016-06-27

    Abstract: A system for data aggregation and distribution comprises a context builder that receives a data request from a consumer, and a producers locator that communicates with producers. A producers filter receives a list of producers and selects producers capable of providing data relevant to context information. A data requests formatter receives the context information, and sends the data request to the selected producers. A data responses validator validates data responses from producers, and a data responses processor processes validated data responses. A data predictor receives processed data responses and context information, and generates data prediction information. A data fusion module receives processed data responses, context information, data prediction information, and data history. The data fusion module combines processed data responses with data prediction information to generate a consolidated data response for the consumer. The data fusion module also considers data prediction information upon receiving a request for predicted data when real-time data is unavailable.

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