547,812 research outputs found
Multimedia big data computing for in-depth event analysis
While the most part of ”big data” systems target text-based analytics, multimedia data, which makes up about 2/3 of internet traffic, provide unprecedented opportunities for understanding and responding to real world situations and
challenges. Multimedia Big Data Computing is the new topic
that focus on all aspects of distributed computing systems that
enable massive scale image and video analytics. During the
course of this paper we describe BPEM (Big Picture Event
Monitor), a Multimedia Big Data Computing framework that
operates over streams of digital photos generated by online
communities, and enables monitoring the relationship between
real world events and social media user reaction in real-time.
As a case example, the paper examines publicly available social media data that relate to the Mobile World Congress 2014 that has been harvested and analyzed using the described system.Peer ReviewedPostprint (author's final draft
FogGIS: Fog Computing for Geospatial Big Data Analytics
Cloud Geographic Information Systems (GIS) has emerged as a tool for
analysis, processing and transmission of geospatial data. The Fog computing is
a paradigm where Fog devices help to increase throughput and reduce latency at
the edge of the client. This paper developed a Fog-based framework named Fog
GIS for mining analytics from geospatial data. We built a prototype using Intel
Edison, an embedded microprocessor. We validated the FogGIS by doing
preliminary analysis. including compression, and overlay analysis. Results
showed that Fog computing hold a great promise for analysis of geospatial data.
We used several open source compression techniques for reducing the
transmission to the cloud.Comment: 6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section
International Conference on Electrical, Computer and Electronics (09-11
December, 2016) Indian Institute of Technology (Banaras Hindu University)
Varanasi, Indi
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