Abstract
In this paper, we present research work related to processing and analysis of big trajectory and Twitter data streams using Apache Storm framework. We present the TrafficStorm application implemented as Storm topology, and describe its implementation on a cluster of commodity computers. TrafficStorm performs processing of big trajectory data streams related to users moving over a street network, as well as tweets issued by users in the area of interest. The experimental evaluation and results in detecting online traffic situation and crowded street segments in a real time, as well as possible explanation of such situation from correlated Twitter messages, demonstrate the feasibility of our approach.
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