G. Argyriou, G. Papadakis, G. Stamoulis, Efi Karra Taniskidou, Nikiforos Pittaras, George Giannakopoulos, Sergio Albani, M. Lazzarini, E. Angiuli, A. Popescu, Argyros Argyridis, Manolis Koubarakis
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引用次数: 2
Abstract
GeoSensor is a novel system that enriches change detection over satellite images with event detection over news items and social media content. GeoSensor faces the major challenges of Big Data: volume (a single satellite image may be a few GBs), variety (its data sources include two different types of satellite images and various types of user-generated content) and veracity, as the accuracy of the end result is crucial for the usefulness of our system. To overcome these three challenges, while offering on-line functionality, GeoSensor comprises a complex architecture that is based on the open-source platform developed in the H2020 project Big Data Europe. Through the presented demonstration, both the effectiveness and the efficiency of GeoSensor's functionalities are highlighted.
GeoSensor是一个新颖的系统，它丰富了对卫星图像的变化检测和对新闻项目和社交媒体内容的事件检测。GeoSensor面临着大数据的主要挑战:体积(单个卫星图像可能是几gb)，多样性(其数据源包括两种不同类型的卫星图像和各种类型的用户生成内容)和准确性，因为最终结果的准确性对我们系统的有用性至关重要。为了克服这三个挑战，在提供在线功能的同时，GeoSensor包含了一个复杂的架构，该架构基于H2020项目Big Data Europe开发的开源平台。通过演示，突出了GeoSensor功能的有效性和高效性。
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