With increasing availability and use of Internet of Things (IoT) devices such as sensors and video cameras, large amounts of streaming data is now being produced at high velocity …
A Padmanabhan, N Agarwal, A Iyer… - … USENIX Symposium on …, 2023 - usenix.org
Video analytics pipelines have steadily shifted to edge deployments to reduce bandwidth overheads and privacy violations, but in doing so, face an ever-growing resource tension …
Real-time video analytics on small autonomous drones poses several difficult challenges at the intersection of wireless bandwidth, processing capacity, energy consumption, result …
X Deng, J Li, E Liu, H Zhang - Journal of Systems Architecture, 2020 - Elsevier
This paper investigates a mobile edge computing environment for video analysis tasks where edge nodes provide their computation capacities to process the computation …
As video camera deployments continue to grow, the need to process large volumes of real- time data strains wide-area network infrastructure. When per-camera bandwidth is limited, it …
E Badidi, K Moumane, F El Ghazi - IEEE Access, 2023 - ieeexplore.ieee.org
Video analytics with deep learning techniques has generated immense interest in academia and industry, captivating minds with its transformative potential. Deep learning techniques …
New paradigms such as Mobile Edge Computing (MEC) are becoming feasible for use in, eg, real-time decision-making during disaster incident response to handle the data deluge …
C Long, Y Cao, T Jiang, Q Zhang - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Multimedia Internet-of-Things (IoT) systems have been widely used in surveillance, automatic behavior analysis and event recognition, which integrate image processing …
Video analytics applications use edge compute servers for processing videos. Compressed models that are deployed on the edge servers for inference suffer from data drift where the …