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Scientific Article details

Title A Spatio-temporal Multimedia Big Data Framework for a Large Crowd
ID_Doc 43515
Authors Sadiq, B; Rehman, FU; Ahmad, A; Rahman, MA; Ghani, S; Murad, A; Basalamah, S; Lbath, A
Title A Spatio-temporal Multimedia Big Data Framework for a Large Crowd
Year 2015
Published
DOI
Abstract Crowdsourced multimedia data poses several challenges when it is collected, stored, indexed, retrieved, and visualized. Examples of crowd source multimedia data are social sensors, vehicle sensors, physical sensors, human sensors, etc. Analyzing such multimodal and diversified crowdsourced data provides very rich understanding about the need of individuals within a crowd. Such understanding makes it possible to tailor services to individuals' needs, also called context-aware services. In this paper, we propose a spatial multimedia big data framework that can collect multimedia data from 1) a very large crowd equipped with multi-sensory smartphones, 2) vehicles, and 3) social networks. A set of multimedia services are offered to users to support their spatio-temporal activities. These include but not limited to 1) simple user interfaces to utilize multimedia services for instant guidance, 2) navigation to points of interests (POI), and 3) efficient and cost effective intra-city rides to users. The big data framework is designed to handle a very large number of multimedia spatio-temporal queries in real-time. The system is a pilot project and will be deployed during the event of Hajj 2015 when over three million pilgrims from all over the world will visit Makkah, Saudi Arabia to perform their Hajj rituals.
Author Keywords Crowdsourcing; Multimedia; Spatio-temporal; Big Data; Smart City
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Conference Proceedings Citation Index - Science (CPCI-S)
EID WOS:000380404600343
WoS Category Computer Science, Information Systems; Engineering, Electrical & Electronic
Research Area Computer Science; Engineering
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