Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/21976
Title: | Mashup Tools for Big Data Analysis in Maritime Surveillance | Authors: | 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 | Keywords: | Maritime Surveillance;Big Data;Mashup Tools;Python;Web Scraping;AIS | Issue Date: | 20-Sep-2020 | Source: | 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 | Journal: | Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV | Conference: | SPIE Security + Defence | Abstract: | 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 |
Appears in Collections: | EXCELSIOR H2020 Teaming Project Publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
20200920_EXCELSIOR_WP10_MASHUPTOOLSFORBIGDATAANALYSISINMARITIMESURVEYLLANCE_V1_PU.pdf | 960.08 kB | Adobe PDF | View/Open |
CORE Recommender
Page view(s) 50
360
Last Week
0
0
Last month
2
2
checked on Dec 3, 2024
Download(s)
406
checked on Dec 3, 2024
Google ScholarTM
Check
Altmetric
This item is licensed under a Creative Commons License