Aerial UAV-IoT Sensing for Ubiquitous Immersive Communication and Virtual Human Teleportation
Jacob Chakareski

TL;DR
This paper proposes an optimization framework for UAV-based IoT sensing to deliver high-quality immersive VR/AR experiences, balancing sampling, transmission, and reconstruction quality under capacity constraints.
Contribution
It introduces a novel joint optimization of UAV sampling rates, scalable data representation, and transmission strategies for immersive VR/AR over UAV IoT networks.
Findings
Optimized sampling rates improve reconstruction quality within capacity limits.
Scalable source-channel coding enhances data adaptivity and error protection.
Use of directional antennas and scheduling boosts transmission efficiency.
Abstract
We consider UAV IoT aerial sensing that delivers multiple VR/AR immersive communication sessions to remote users. The UAV swarm is spatially distributed over a wide area of interest, and each UAV captures a viewpoint of the scene below it. The remote users are interested in visual immersive navigation of specific subareas/scenes of interest, reconstructed on their respective VR/AR devices from the captured data. The reconstruction quality of the immersive scene representations at the users will depend on the sampling/sensing rates associated with each UAV. There is a limit on the aggregate amount of data that the UAV swarm can sample and send towards the users, stemming from physical/transmission capacity constraints. Similarly, each VR/AR application has minimum reconstruction quality requirements for its own session. We propose an optimization framework that makes three contributions…
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Taxonomy
TopicsAdvanced Vision and Imaging · Image Enhancement Techniques · Video Surveillance and Tracking Methods
