Towards autonomous semantic stream fusion for distributed video streams

Video streams are becoming ubiquitous in smart cities and traffic monitoring. Recent advances in computer vision with deep neural networks enable querying a rich set of visual features from these video streams. However, it is challenging to deploy these queries on edge devices due to the resource intensive nature of the computing operations of this sort. Hence, this paper will demonstrate our approach in pushing these computing operations closer to the video stream sources via autonomous stream fusion agents. These agents will facilitate an edge computing paradigm that enables edge devices to utilize its computing resources to serve federated queries over video streams. Our demonstration shows that edge devices can significantly alleviate the bottleneck of the centralized server in dealing with distributed video streams.