The vision of the SliceNet ‘Connected Ambulance’ eHealth use case combines many advanced technologies that come together to enable the delivery of better life enhancing outcomes for patients.
The recent demo by DellEMC at EuCNC2019 illustrated the potential of 5G, Edge and machine learning innovation applied to an eHealth use case by examining the scenario of possible stroke victims at a remote location. The demo showed the seamless composition and onboarding of the eHealth slice and how edge computing with hardware acceleration can assist with a continuous collection, processing and streaming of patient data that shortens the time to assess potential stroke victims. The workload is real-time AI image processing which means both network and compute intensive and can be addressed by 5G technologies enablers such as QoS-aware network slicing, edge computing and hardware acceleration. The demo also implemented the monitoring feature to show the performance (latency, throughput) of the eHealth slice running in the testbed.
Through their involvement in the H2020 SliceNet Project, SliceNet partners DellEMC, RedZinc and CIT SIGMA Research Group are amongst those researching how 5G network slicing can transform prehospital medical emergencies for a wide range of urgent clinical treatment pathways, including stroke.
As part of this research, SIGMA have developed and deployed an innovative prototype of their machine-learning TeleStroke Assessment service at the Dell EMC testbed in Ovens, Co Cork.
SliceNet partner RedZinc have developed video streaming technology over 4G and 5G along with a specialised hands device free camera to carry dedicated QoS video from the scene of an emergency or community health issue back to an expert medical advisor at a hospital hot desk.
From this slicing network application, SliceNet is aiming to provide quality of service (QoS) guarantees through end-to-end (E2E) network slicing over future 5G networks in many vertical applications including eHealth.