ECML PKDD 2014: Machine Learning and Knowledge Discovery in Databases pp 520-523 | Cite as
Heterogeneous Stream Processing and Crowdsourcing for Traffic Monitoring: Highlights
Conference paper
Abstract
We give an overview of an intelligent urban traffic management system. Complex events related to congestions are detected from heterogeneous sources involving fixed sensors mounted on intersections and mobile sensors mounted on public transport vehicles. To deal with data veracity, sensor disagreements are resolved by crowdsourcing. To deal with data sparsity, a traffic model offers information in areas with low sensor coverage. We apply the system to a real-world use-case.
Keywords
smart cities crowdsourcing event pattern matching traffic stream processing big dataPreview
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