Abstract: An illustrative mobile device includes a data storage configured to at least temporarily store visual information and at least one processor that is configured to determine whether to request visual information processing from a network with which the mobile device may communicate. The processor is configured to determine a mobile device condition and a network condition. The processor determines a type of feature from the visual information to use for classification based on the determined mobile device and network conditions. The processor is configured to classify the visual information based on the determined type of feature and determine a confidence indicator based on the classification. The processor determines whether to request visual information processing from the network based on the determined confidence indicator.

Abstract: An illustrative mobile device includes a data storage configured to at least temporarily store visual information and at least one processor that is configured to determine whether to request visual information processing from a network with which the mobile device may communicate. The processor is configured to determine a mobile device condition and a network condition. The processor determines a type of feature from the visual information to use for classification based on the determined mobile device and network conditions. The processor is configured to classify the visual information based on the determined type of feature and determine a confidence indicator based on the classification. The processor determines whether to request visual information processing from the network based on the determined confidence indicator.

Abstract: A method and system for increasing accuracy in estimating average time taken to travel through a chosen road segment is provided. The method includes determination of time taken by one or more vehicles to travel through the road segments. Further, correlated road segments for which time taken to travel through the correlated road segments is correlated with the time taken to travel through the chosen road segment, are identified. A data repository stores a list of the one or more correlated road segments. Among the correlated road segments, one or more preferred road segments that increases the accuracy in determining the average time taken to travel through the chosen road segment, is determined by at least one processor. Further, the processor estimates the average time taken to travel through the chosen road segment using, data corresponding to time taken to travel through, the preferred road segments and the chosen road segment.

Abstract: A method and system is provided for predicting at a current time “t”, a time that may be taken to travel between plurality of locations, at a future time-point “t+?”. The method includes determining deterministic component “?t+?” and predicting random fluctuation component “ylt+?”, of the time that may be taken to travel between the plurality of locations at the future time-point “t+?”. The deterministic component “?t+?” and the random fluctuation component “ylt+?” are added to predict the time that may be taken to travel between the plurality of locations, at the future time-point “t+?”.

Abstract: A method and system for increasing accuracy in estimating average time taken to travel through a chosen road segment is provided. The method includes determination of time taken by one or more vehicles to travel through the road segments. Further, correlated road segments for which time taken to travel through the correlated road segments is correlated with the time taken to travel through the chosen road segment, are identified. A data repository stores a list of the one or more correlated road segments. Among the correlated road segments, one or more preferred road segments that increases the accuracy in determining the average time taken to travel through the chosen road segment, is determined by at least one processor. Further, the processor estimates the average time taken to travel through the chosen road segment using, data corresponding to time taken to travel through, the preferred road segments and the chosen road segment.

Abstract: A method and system is provided for predicting at a current time “t”, a time that may be taken to travel between plurality of locations, at a future time-point “t+?”. The method includes determining deterministic component “?t+?” and predicting random fluctuation component “y1t+?”, of the time that may be taken to travel between the plurality of locations at the future time-point “t+?”. The deterministic component “?t+?” and the random fluctuation component “y1t+?” are added to predict the time that may be taken to travel between the plurality of locations, at the future time-point “t+?”.