AI-Driven Smart Elderly Care: Innovations and Solutions

Dear Colleagues,

This topic focuses on emerging artificial intelligence (AI) technologies and their transformative potential in the domain of smart elderly care. With the global ageing population projected to double by 2050, there is a pressing need to design and implement intelligent systems that can support independent living, remote monitoring, and predictive health management for older adults. The integration of AI with Internet of Things (IoT), edge computing, robotics, and wearable technologies has enabled the development of smart environments that can assist elderly individuals in maintaining autonomy, improving safety, and enhancing quality of life.

This topic aims to explore the latest innovations, practical deployments, and theoretical advancements in AI-enabled elderly care systems, including personalised assistive technologies, emotion-aware computing, ethical and privacy-preserving frameworks, and data-driven decision support models.

Topics of interest include, but are not limited to the following:

• AI-driven predictive health analytics and anomaly detection;
• IoT-enabled ambient assisted living (AAL) systems;
• AI and robotics in elderly rehabilitation and surgical assistance;
• Telemedicine and virtual healthcare platforms for ageing populations;
• Privacy-preserving and secure AI models in elderly care environments;
• Generative AI and its application in mental health support for seniors;
• Emotion-aware computing and socially assistive AI companions;
• Wearable sensing technologies integrated with machine learning models;
• Natural language processing (NLP) interfaces for elderly engagement;
• Ethical, regulatory, and policy considerations in AI-based gerontology.

We encourage submissions from multiple disciplinary lenses, including healthcare informatics, human-centred computing, AI ethics, clinical engineering, cybersecurity, and digital health. We welcome original research articles, reviews, technical developments, and application case studies that advance the state of knowledge in this crucial area of intelligent systems for elderly care.

Dr. Mahmoud Elkhodr
Prof. Dr. Ergun Gide
Topic Editors