Telehealth Remote Monitoring scale: A Cloud based virtual collaboration approach

Telehealth has become widespread and has now become an integral part of the standard of care for many patients and doctors. Telehealth has filled gaps in healthcare delivery enabling multi-site remote monitoring, remote diagnosis, virtual consultations, and even home monitoring However, adoption has been constrained by technological and operational issues, creating a growing demand for telehealth in new locations. As the demand for telehealth continues to increase in new locations, new ways to deliver telehealth services will be needed. In some cases, these new ways to deliver telemedicine services may not require the same level of infrastructure that has been accepted in the past. Today, telehealth is facilitated by a variety of platforms, including online video chat and text, phone and video conferencing, and provider-premise equipment. Some of these platforms are built on the cloud, while others are independent of the cloud. Operating independently of the cloud provides additional flexibility, allowing developers to build and launch their products faster. However, building on independent platforms also has its challenges.

Building a Telehealth Head Start

The Telehealth remote monitoring reference implementation demonstrates a cloud-based containerized telehealth service using the powerful Intel Collaboration Suite for WebRTC (Intel CS for WebRTC) and the Open Visual Cloud software stacks. It provides a virtual collaboration infrastructure that is delivered on an Intel Kubernetes-optimized Intel Smart Edge. The media server included in the Open WebRTC Toolkit coordinates sessions between users. And the web application interface provides a way for users, for example physicians, patients, device specialists, and healthcare professionals, to facilitate connecting, viewing, and communicating via a range of possible end devices.

The ability to have physicians, nurses and other healthcare professionals work together on the same screen, video chat and share screen real-time data, has the potential to revolutionize how we practice medicine. Today, these interactions are typically done one-on-one or in small groups. This limits the potential for complex team discussions and the effective sharing of information.

The functionality is broken down into public front-end and service containers, as well as a steering wheel graphics package made available through the Intel(r) developer directory. This separation of features gives you the ability to try, learn, and update features while reusing the infrastructure across different use cases. The components of the Intel Collaboration Suite for WebRTC (Intel CS for WebRTC) can be integrated directly with the building blocks of the Open Visual Cloud pipeline for real-time video analytics. This means that customers don't need to make a choice between advanced video processing and sharing, or advanced collaboration features. They can have the best of both worlds, with the added benefits of advanced video processing and sharing. This is possible because Intel CS for WebRTC and the Open Visual Cloud pipeline are built on the same platform, which enables them to communicate with each other at the operating system level.

Curating the Right Ingredients

The Telehealth reference implementation uses the video conferencing sample from the Open Visual Cloud project, ready for use in Kubernetes, Smart Edge, locally, and optimized for the Intel network edge. As a cloud workload, the same building blocks can be synthesized to reproduce the same functionality - let's take a closer look at its components.

The open visual cloud/ xeon-ubuntu1804-service-owt container carries most of the streaming framework. The detailed configuration of this component here is the first important configuration step that we need to do. The videoconferencing sample is a scripted example of how to initialize basic components in a service-owt container.

Cloud Native at the Edge

The main goal of the reference implementation is to demonstrate how these cloud capabilities can be deployed locally in a way that will provide global coverage without major configuration changes. The same brokerage server used here can be installed on a mobile operator or cloud service provider network for coverage and scale or deployed to provide on-site remote monitoring capabilities regardless of Internet connectivity or quality. It can also run on any platform that can be delivered to the site as part of a simplified IT package.

Conclusion

Remote work and the rise of video and voice communication have accelerated the need for real-time communication and collaboration. But the traditional architecture of a client-server model is no longer fast enough. Today’s most advanced applications need the ability to process streams in real time, often from multiple sources. At the same time, businesses are looking for ways to reduce the cost and complexity of their video infrastructure without giving up performance.

Most developers today have had to build apps that support real-time communication. The result is a growing demand for high performance, low-latency applications. In the past, businesses had to invest in expensive dedicated video infrastructure, but now they can use the same tools and techniques that developers use every day. This means they can create high-quality, real-time applications without spending a fortune on infrastructure.

This reference implementation provides unique advantages for testing, integrating, and deploying these capabilities in existing or new software products, devices, or services. Visit the Telehealth Remote Monitoring Reference Implementation to learn more and download. See the Intel Developer Directory for software and tools for developing and deploying solutions optimized for Intel^®architecture. Visit www.Intel.com Telemedicine page for more details: https://www.intel.com/content/www/us/en/healthcare-it/telemedicine.html