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The incorporation of Artificial Intelligence (AI) with the Internet of Things (IoT) and Cyber-Physical Systems (CPS) offers a significant opportunity in healthcare, especially in improving disease detection and patient well-being. This survey offers a comprehensive overview of recent advancements in AI-driven IoT-CPS for healthcare applications, focusing on enhancing the Quality of Life (QoL) for elderly individuals through real-time health monitoring, disease prediction, and emergency response systems. The survey reviews relevant studies and developments in AI-driven IoT-CPS, specifically in healthcare. The literature selected includes studies on real-time health monitoring, disease detection, and data security. Significant contributions from peer-reviewed journals and conferences are analysed, highlighting advancements and research gaps. Key findings include improvements in IoT and CPS security and progress in real-time health monitoring. However, challenges like accuracy limitations and inadequate security measures in AI-driven IoT-CPS solutions are identified. It emphasizes the requirement of more study and creativity to deal with these challenges and develop reliable systems that provide accurate and secure real-time health monitoring. The survey emphasizes the promising potential of AI-driven IoT-CPS in transforming healthcare while acknowledging existing challenges. Future research should focus on overcoming these challenges through innovative solutions and robust security measures. By addressing these issues, AI-driven IoT-CPS can fulfil their potential in improving disease detection, patient care, and overall healthcare outcomes.
Khalse et al. (Thu,) studied this question.