Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο:
https://hdl.handle.net/20.500.14279/21976
Τίτλος: | Mashup Tools for Big Data Analysis in Maritime Surveillance | Συγγραφείς: | Melillos, George Themistocleous, Kyriacos Danezis, Chris Michaelides, Silas Hadjimitsis, Diofantos G. Jacobsen, Sven Tings, Björn |
Major Field of Science: | Engineering and Technology | Field Category: | Civil Engineering | Λέξεις-κλειδιά: | Maritime Surveillance;Big Data;Mashup Tools;Python;Web Scraping;AIS | Ημερομηνία Έκδοσης: | 20-Σεπ-2020 | Πηγή: | Proceedings Volume 11542, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV | Volume: | 11542 | Issue: | 1154208 | Project: | ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment | Περιοδικό: | Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV | Conference: | SPIE Security + Defence | Περίληψη: | The growth of big data and its popularity in maritime surveillance has increased at an exponential rate. The amount of maritime information being collected every minute around the world exceeds the capacity of traditional databases. The development of real-time, Geospatial Web Applications e.g., MarineTraffic and VesselFinder AIS vessel tracking web sites, provide us with huge sets of structured and unstructured data that are too complex for traditional data-processing software. The aim of this paper is to exploit the benefits of query and mashup amounts of maritime data using mashup tools as a result to create a single, unique visualization. The results show that using mashup techniques in maritime surveillance could be used to monitor, compare, combine, manipulate and analyse Big Maritime data. Therefore, research on Maritime Data offers a huge potential and an opportunity to benefit from the advantages. | URI: | https://hdl.handle.net/20.500.14279/21976 | DOI: | 10.1117/12.2573749 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Conference Papers | Affiliation: | Cyprus University of Technology ERATOSTHENES Centre of Excellence DLR - German Aerospace Center |
Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | EXCELSIOR H2020 Teaming Project Publications |
Αρχεία σε αυτό το τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
---|---|---|---|---|
20200920_EXCELSIOR_WP10_MASHUPTOOLSFORBIGDATAANALYSISINMARITIMESURVEYLLANCE_V1_PU.pdf | 960.08 kB | Adobe PDF | Δείτε/ Ανοίξτε |
CORE Recommender
Page view(s)
395
Last Week
0
0
Last month
32
32
checked on 14 Μαρ 2025
Download(s)
436
checked on 14 Μαρ 2025
Google ScholarTM
Check
Altmetric
Αυτό το τεκμήριο προστατεύεται από άδεια Άδεια Creative Commons