Abstract: A method of a route prediction system utilizing real-time mobile communication network data. The method includes receiving a route request originating from a connected vehicle, the route request identifying a route, determining segments for the route, localizing mobile communication network resources to the segments, determining key performance indicators for the segments based on at least a current offline model, and sending predicted service level indicators (SLIs) for the segments to the connected vehicle.

Abstract: A method provides route information to a connected vehicle in a brokered information prediction system. The method includes determining available mobile communication networks that can provide real-time mobile communication network data, querying a first available mobile communication network to provide key performance indicators for a route for a connected vehicle, determining service level indicators for the route based on received key performance indicators for the route where the key performance indicators meet defined thresholds, and sending predicted service level indicators for the route to the connected vehicle.

Abstract: A method of a route prediction system utilizing real-time mobile communication network data. The method includes receiving a route request originating from a connected vehicle, the route request identifying a route, determining segments for the route, localizing mobile communication network resources to the segments, determining key performance indicators for the segments based on at least a current offline model, and sending predicted service level indicators (SLIs) for the segments to the connected vehicle.

Abstract: A route prediction system implements a method that utilizes real-time mobile communication network data including receiving real-time mobile communication network data. The method further includes aggregating the real-time mobile communication network data with historical data to form a training set, filtering the training data set for relevance to servicing route predictions for connected vehicles, training a plurality of offline models using the filtered training data set, and selecting a best performing propagation model from the plurality of offline models.

Abstract: A method provides route information to a connected vehicle in a brokered information prediction system. The method includes determining available mobile communication networks that can provide real-time mobile communication network data, querying a first available mobile communication network to provide key performance indicators for a route for a connected vehicle, determining service level indicators for the route based on received key performance indicators for the route where the key performance indicators meet defined thresholds, and sending predicted service level indicators for the route to the connected vehicle.

Abstract: A method for rendering a SVG content is provided. The method includes identifying one or more SVG tags and attributes in the SVG content by parsing the SVG content. Further, the method includes converting each of the identified SVG tags and attributes to a unique binary stream for obtaining a binary representation of the SVG content. The unique binary stream represents each of the SVG tags and the attributes. Further, the method includes storing the binary representation of the SVG content. Further, the method includes dynamically rendering the SVG content by parsing the binary representation.

Abstract: A method for rendering a SVG content is provided. The method includes identifying one or more SVG tags and attributes in the SVG content by parsing the SVG content. Further, the method includes converting each of the identified SVG tags and attributes to a unique binary stream for obtaining a binary representation of the SVG content. The unique binary stream represents each of the SVG tags and the attributes. Further, the method includes storing the binary representation of the SVG content. Further, the method includes dynamically rendering the SVG content by parsing the binary representation.