An In-Depth Context-Awareness Framework for Pervasive Video Cloud

We claim that context-awareness for big data should be more in-depth than that of classical one, due to complexities of big data. Intelligent video data processing based on video cloud plays an important role for some applications such as public security and transportation. The existing work on context-awareness can not work properly on pervasive video cloud due to the intrinsic complexities of big video data. Therefore, in this paper we propose an in-depth context-awareness framework for pervasive video cloud in order to know the underlying contexts in big video data, based on deep learning techniques. We have conducted initial evaluations to show the effectiveness of the proposed approach, including the prediction of workload for cloud nodes, and the recognition of targets in the video at real time.