Conference paper Open Access

Big Data Management and Analytics for Mobility Forecasting in datAcron

Christos Doulkeridis; Nikos Pelekis; Yannis Theodoridis; George Vouros

The exploitation of heterogeneous data sources offering very large historical and streaming data is important to increasing the accuracy of operations when analysing and predicting future states of moving entities (planes, vessels, etc.). This article presents the overall goals and big data challenges addressed by datAcron on big data analytics for time-critical mobility forecasting.

Files (135.5 kB)
Name Size
EuroPro_paper_02.pdf
md5:73cbcf58a6eaadf268d93741a75cf98a
135.5 kB Download
9
5
views
downloads
All versions This version
Views 99
Downloads 55
Data volume 677.6 kB677.6 kB
Unique views 99
Unique downloads 55

Share

Cite as