IEEE COINS | IoT , AI, and Big Data for Healthcare Track

IEEE COINS 2021


Artificial Intelligence



IEEE COINS is the premier conference devoted to omni-layer techniques for smart IoT systems, by identifying new perspectives and highlighting impending research issues and challenges.
The e-Health and Wearable IoT track at COINS seeks the latest research advancements in the convergence of automation technology, artificial intelligence, biomedical engineering, wearable and mobile computing, Internet-of-Things, and healthcare.
Topics of interest include, but are not limited to, the following:
• Internet of things for medical and healthcare applications
• Mobile and e-Health sensing
• Wearable, outdoor and home-based sensors
• Novel devices and circuits, and architectural support for e-health
• Printable electronics
• Harvesting management and optimization
• Nano-CMOS and Post-CMOS based sensors, circuits, and controller
• Wearable and implantable computing and biosensors
• Cloud-enabled body sensor networks
• Secure middleware for eHealth and IoT
• Energy-efficient PHY/MAC and networking protocols for eHealth applications
• Reprogrammable and reconfigurable embedded systems for eHealth
• eHealth traffic characterization
• Biomedical signal processing
• AI-based decision support systems for healthcare
• eHealth oriented software architectures (Agent, SOA, Middleware, etc.)
• Big-data analytics, machine learning algorithms, and scalable/parallel/distributed algorithms
• Theory and practice of engineering semantic e-health systems, especially methods, means and best cases
• Fog computing/Edge clouds for health care cloud resource allocation and monitoring
• Privacy-preserving and Security approaches for large scale analytics
• Privacy-Preserving Machine Learning (PPML) and Multi-party computation (MPC) techniques
• AI bias reduction approaches for mhealth and ehealth applications and ethical issues regarding nudging
• Blockchain: Opportunities for health care
• Fault tolerance, reliability, and scalability
• Autonomic analysis, monitoring and situation alertness
• Case studies of smart eHealth architectures (telemedicine applications, health management applications, etc.)