Operating in the rural area where the counties of Shropshire and Worcestershire meet, ‘West Mercia Rural 5G’ will explore infrastructure challenges when planning, building and operating a rural 5G network and look at how 5G can enhance services for the benefit of residents, particularly researching 5G enabled health and social care applications.
Led by Worcestershire County Council, key partners on the network side are Airband and BT who will plan, build and operate the 5G network. Local NHS organisations alongside Worcestershire County Council and Shropshire Council will work on the health and social care applications. The University of Worcester, University Centre Shrewsbury, and West Midlands Academic Health Science Network are providing their expert support across the project.
More about this Project
The key partners on the network side are Airband and BT with further support provided through the Worcestershire 5G testbed. The project explores a new model to demonstrate how building mobile network infrastructure in rural areas could be done more cost effectively and at increased pace. In addition to building a new 5G Standalone network the project aims to make use of access to the public 4G network and private 4G and 5G Non-standalone network to allow use cases to understand performance across the technologies.
The local NHS organisations alongside Shropshire Council and Worcestershire County Council and private sector partners are leading on the development of the health and social care applications, with the University of Worcester, University Centre Shrewsbury and West Midlands Academic Health Science Network are providing their expert support to deliver new health and social care technology enabled pilots working with residents, care homes, community hospitals and doctors surgeries.
Two specific use cases include the ‘use of XR to support remote monitoring of patients’ and the ‘Connected Worker’ utilising wearable video & mobile telemedicine, with other use cases in development.
As an example, the XR solution from project partner TalkOut VR provides an augmented view of a patient, utlising biometric data that can be used in any place that human motion is desired to be studied, such as in the study and analysis of physical therapy, Parkinson’s Disease or in the study of athletes in sports performance contexts. AR headsets capture image and depth data, which then use that information to build a body model on the server, in real time, using GPU-based deep neural networks. This data will then be used to overlay around a person with body model information and biostatistics gathered from analysis of that body model.