With the development of smart sensorial media, things, edge analytics along with Artificial Intelligence (AI) and cloud technologies, “Connected healthcare” is getting remarkable consideration from academia, the governments, the industry, and the healthcare community. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality with a massive amount of data and numerous services. However, because of the massive connectivity of IoT-connected devices in providing numerous connected health services, it becomes a computation-intensive and storage burden at each edge device. To address this challenge, edge computing along with AI provides powerful computation services and massive data acquisition at edge networks in an intelligent manner for autonomous decision-making, which is quite impossible for individual human analysts. The edge-IoT services can provide a high quality of experience to physicians, clinics, and other caregivers anytime and from anywhere seamlessly. Similarly, with the outbreak of COVID-19, Artificial Intelligence (AI) has gained significant attention by utilizing its machine learning algorithms for quality patient care. However, the convergence of Edge, IoT, and AI can provide new opportunities for both technologies, as it can play a significant role in smart healthcare by offering a better insight into healthcare data to support affordable personalized care.

This workshop aims to report high-quality research on recent advances in various aspects of smart connected health, more specifically to the state-of-the-art approaches, methodologies, and systems in the design, development, deployment, and innovative use of networked services, tools, and technologies for smart connected health. Authors are solicited to submit complete unpublished papers in the following, but not limited to the following topics of interest.:

Explainable AI (XAI) and predictive edge analytics for COVID-19
Edge AI-assisted COVID-19 and alike detection/diagnosis systems
AI-centric Mobile Edge Computing (MEC) approach for Connected health
AI-enabled IoT-edge data analytics for Connected Health
AI-enabled edge data fusion for Connected Health
ML-driven driven edge approach to Connected Health
Deep Learning-based networked applications, techniques, and testbeds for Health
AI-driven multi-access edge computing approach for Connected Health
EdgeAI- empowered big data Analytics and cognitive computing for connected health monitoring
Advanced AIIoT convergent services, systems, infrastructure, and techniques for healthcare
EdgeAI-supported IoT data analytics for smart healthcare
New opportunities, challenges, case studies, and applications of Edge-AI for Connected healthcare
Security, Privacy, and Trust of Edge-AI for Connected health
Submission Guidelines

Submission guidelines: Full-length papers of 6 pages in length.
All submissions should be done via https://edas.info/N31201, please choose Workshop on Edge-AI and IoT for Connected Health (GC 2023 Workshop - Edge-AI-IoT)
Please make sure to follow the "Author and Submission Guidelines" for submissions (see the link on https://globecom2023.ieee-globecom.org/call-workshop-papers) and https://edas.info/N31201.


IEEE GLOBECOM 2023 Workshop on Workshop on Edge-AI and IoT for Connected Health

Accepted papers will be published by IEEE in the workshop proceedings along with the IEEE GLOBECOM 2023 proceedings.

Extended versions of some selected accepted papers will be invited to submit to a special issue of Q1-ISI-indexed Journals

Important dates

Workshop Papers Due: 15 July 2023
Workshop Papers Acceptance Notification: 01 September 2023
Final Camera-Ready Paper Due: 01 October 2023



Organizing Co-chairs

Shamim, Nadra, Victor