Enabling MEC platforms in Healthcare & Smart Hospitals
Emerging healthcare use cases require efficient deployment of AI inferencing at the edge. For successful adoption, a deployment platform should meet throughput and latency requirements across demanding workloads, such as medical imaging, patient monitoring, digital pathology and telemedicine, while providing manageability at scale. This talk presents the challenges in deploying a MEC based platform for smart hospital use cases and a reference implementation customized for digital pathology use case. An OpenVINO based inferencing engine model server is onboarded and managed across heterogenous compute & network architectures for video analytics across various hospital’s needs. This talk further delves into video analytics requirements of the Edge platform to satisfy necessities Operating Room of the Future at scale utilizing Kubernetes and cloud native applications.
