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Agora: Democratizing Low Latency Wireless for Remote
XR Medical Collaboration

Project Agora aims to help deliver medical expertise when and where it's needed through XR – enabled by overcoming technical barriers to deployable low-latency wireless networking.

Image Source: MediView

Specialized, high-level medical expertise is a scarce resource, and is often not available at the time and location it is urgently needed. Extended reality (XR) technology could bring experts to where they are needed, assisting on-site personnel and potentially making the difference that enables positive patient outcomes. However, such real-time experiences critically depend on the latency of interaction, and today’s wireless networks have relatively high and variable latency.

Project Agora is creating innovative technology that democratizes wireless low-latency, making it more widely deployable for many users and applications through improved spectrum efficiency. Leveraging this technology, it is building XR systems that democratize access to high-level medical expertise, making them much more widely available for medical collaboration.

Agora is made possible by the NSF 24-545 Breaking Low Program (Awards 2454014, 2454015).

Areas of Innovation

Medical Applications

An XR medical training application and extensions to the FDA-cleared MediView AR-guided surgical platform to enable remote XR collaboration and leverage low latency communication capabilities.

XR Runtime

An OpenXR runtime architecture that promotes application-runtime-network co-design by actively tolerating network latency with offloaded components, adapting demand to network conditions, and informing the network about heterogeneous requirements.

Transport Protocol

A latency-aware multipath protocol that optimizes fine-grained steering of individual packets onto multiple service types, including latency- and bandwidth-optimized wireless services.

Wireless Service

A fine-grained dynamic radio resource controller for 5G networks that satisfies both low-latency and high-throughput demands in parallel, optimizing spectral efficiency.