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Towards a distributed framework to analyze multimodal data

Abstract:

Data synchronization gathered from multiple sensors and its corresponding reliable data analysis has become a difficult challenge for scalable multimodal learning systems. To tackle this particular issue, we developed a distributed framework to decouple the capture task from the analysis task through nodes across a publish/subscription server. Moreover, to validate our distributed framework we build a multimodal learning system to give on-time feedback for presenters. Fifty-four presenters used the system. Positive perceptions about the multimodal learning system were received from presenters. Further functionality of the framework will allow an easy plug and play deployment for mobile devices and gadgets.