Data Reduction Techniques Applied on Automatic Identification System Data
In recent years, the constant increase of waterway traffic generates a high volume of Automatic Identification System data that require a big effort to be processed and analyzed in near real-time. In this paper, we analyze an Automatic Identification System data set and we propose a data reduction technique that can be applied on Automatic Identification System data without losing any important information in order to reduce it to a manageable size data set that can be further used for analysis or can be easily used for Automatic Identification System data visualization applications.
KeywordsAIS data Data reduction techniques Data analysis AIS data visualization Intelligent transport systems
This work has been partially supported by COST Action IC1302: Semantic keyword-based search on structured data sources (KEYSTONE); we particularly acknowledge the support of the grant COST-STSM-IC1302-36978: “Curating Data Analysis Workflows for Better Workflow Discovery”.
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