Enabling MEC platforms in Healthcare & Smart Hospitals
summary
A containerized edge platform demonstrates deployable AI inferencing for digital pathology using an OpenVINO model server and DLStreamer pipeline server on Kubernetes, abstracting underlying Intel CPU/GPU/accelerator variants and exposing telemetry via Prometheus exporters. The team ships a digital pathology reference implementation and private wireless kit, integrates TPM/SGX/TDX for hardware-backed trust, and supports lifecycle management plus federated-learning hooks; deployments run as microservices, claim low-latency video analytics at hospital scale, and are available as open-source experience kits.
AI-written summary · about
chapters (14)
- 0:00Start
- 6:25Smart Hospitals- Need for Edge Computing
- 9:28Delivering Cloud Native Platforms for the Edge
- 12:42Intel® Smart Edge: MEC, Apps, and More
- 14:22Intel Smart Edge Open Experience Kits
- 19:14Intel Smart Edge Open Developer Experience Kit
- 21:13Addressing Al Complexity-OpenVINO
- 21:50OpenVINO Model Server
- 23:25Digital Pathology with Edge Computing
- 24:27Al Model Manageability & Service Orchestration- At Scale
- 25:30Connected Healthcare with Intel Smart Edge
- 27:32Further Applications
- 29:11Check it Out-Telehealth Reference
- 29:46Check it Out-Telepathology Reference
related talks
18mArchitecting Intelligent Platforms
24mDemo of Kubernetes at the Edge for AI Model Deployments
45mAIoT Ops - Using Kubernetes and ML Ops to Build Edge ML Applications
49mEnable IoT with Edge Computing and Machine Learning
52mMachine Learning in IoT Applications
25mEmpowering AI-Driven Drug Discovery: Overcoming Challenges in Building a ML Platform on Kubernetes
43mGo Microservices for ML at the Edge
29mCloud and Edge: Price, Performance and Privacy Considerations in IOT