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IEEE COINS 2021 : IEEE COINS | IoT , AI, and Big Data for Healthcare Track | |||||||||||||
Link: https://coinsconf.com/ | |||||||||||||
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Call For Papers | |||||||||||||
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.) |
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