Call for Papers

AI-Driven Security and Modeling for Wireless and Mobile Healthcare Systems (AI-SMARTHealth 2026)

Workshop co-located with the International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM 2026)

Overview

Digital health is rapidly transforming modern healthcare through the integration of wireless and mobile technologies, including wearable devices, body area networks, IoT-based medical systems, and edge–cloud infrastructures. These systems enable continuous monitoring, real-time analytics, and personalized care beyond traditional clinical environments.

At the same time, the increasing reliance on distributed, resource-constrained, and data-intensive wireless healthcare systems introduces major challenges in security, privacy, reliability, and performance. Vulnerabilities in medical IoT devices, adversarial threats against AI models, and strict requirements in latency, energy efficiency, and Quality of Service (QoS) make the design of such systems particularly complex.

Artificial Intelligence (AI), combined with network-aware modeling and system-level optimization, offers powerful tools to address these challenges. However, integrating AI into wireless healthcare systems raises new issues related to scalability, robustness, interpretability, and secure deployment.

Workshop Scope

The AI-SMARTHealth 2026 workshop aims to bring together researchers and practitioners from wireless and mobile systems, AI, cybersecurity, and healthcare technologies to explore novel approaches for the design, modeling, analysis, and deployment of secure and intelligent digital-health systems.

The workshop particularly encourages contributions that:

• Bridge AI and wireless/mobile system design
• Address network-aware intelligence and performance constraints
• Propose secure and scalable architectures for healthcare applications
• Include modeling, simulation, or experimental evaluation

Building on the success of previous initiatives (e.g., AI-EFD’25 at IEEE HealthCom), this edition places stronger emphasis on wireless infrastructures, system modeling, and performance analysis, in line with MSWiM’s core themes.

Topics of Interest

Topics include, but are not limited to:

Wireless and Mobile Healthcare Systems

• Wireless sensor networks, body area networks, and IoT in healthcare
• Communication protocols for mobile health systems
• Resource allocation, routing, and scheduling in healthcare networks
• QoS/QoE provisioning for healthcare applications
• Energy-efficient and reliable communication in medical systems

AI for Wireless and Mobile Healthcare Systems

• AI-driven health monitoring and decision support over wireless systems
• Machine learning and deep learning for biomedical signals and images
• Reinforcement learning for adaptive and personalized healthcare
• Network-aware AI and communication-efficient learning

Cybersecurity and Privacy

• Threat detection and anomaly detection in healthcare networks
• Security of IoT medical devices and wearable systems
• Adversarial machine learning in healthcare
• Privacy-preserving techniques (federated learning, differential privacy, homomorphic encryption)
• Secure data sharing and access control

Distributed and Edge Intelligence

• Edge computing and federated learning in healthcare systems
• On-device intelligence for mobile and wearable devices
• Real-time analytics under resource constraints
• Distributed AI for large-scale healthcare deployments

Modeling, Simulation, and Performance Analysis

• Modeling and simulation of wireless healthcare systems
• Performance evaluation (latency, reliability, scalability, energy efficiency)
• Analytical and stochastic modeling of healthcare networks
• Simulation frameworks for large-scale IoT healthcare systems
• Trade-offs between communication, computation, and learning

Sensing and Data Integration

• Multi-modal data fusion (physiological, behavioral, environmental)
• Ambient intelligence and context-aware healthcare
• Integration of heterogeneous sensing platforms

Trustworthy and Explainable AI

• Explainability and interpretability in healthcare AI
• Bias, fairness, and ethical considerations
• Human-in-the-loop decision systems

System Evaluation and Deployment

• Benchmarking and datasets for wireless healthcare systems
• Real-world deployment and experimental validation
• Robustness, reliability, and user acceptance

Emerging Directions

• Digital twins for healthcare systems
• Extended reality (XR) in healthcare environments
• AI-driven telehealth and remote monitoring

Submission Guidelines

• Papers must be original and unpublished, and not submitted elsewhere.
• Submissions should follow the MSWiM conference formatting guidelines (IEEE format).
• Full papers are expected to be 6-8 pages, including references.
• All submissions will undergo peer review based on originality, technical quality, relevance, and clarity.

Accepted papers will be included in the MSWiM 2026 Workshop Proceedings.

Important Dates

• Paper Submission Deadline: July 17, 2026
• Notification of Acceptance: August 4, 2026
• Camera-Ready Submission: August 14, 2026
• Workshop Date: October 26, 2026 (co-located with MSWiM 2026)

Organizers

· Moustafa Fayad, Junior Professor (chaire de professeur junior), SINERGIES (UR 4662), University of Marie & Louis Pasteur, France, moustafa.fayad@univ-fcomte.fr

· Ahmed Mostefaoui, Associate Professor - HDR, Femto-ST (UR 6174), University of Marie & Louis Pasteur, France, amostefa@femto-st.fr

· Mohammed Amine Merzoug, Associate Professor – HDR, Department of computer science, University of Batna 2, Algeria, amine.merzoug@univ-batna2.dz

Contact

For inquiries, please contact the workshop organizers.