AI-Driven Smart Elderly Care: Innovations and Solutions

Topic Information

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

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	5.0	6.9	2020	20.7 Days	CHF 1600	Submit
Geriatrics geriatrics	2.1	3.4	2016	19.5 Days	CHF 1800	Submit
Journal of Ageing and Longevity jal	-	-	2021	23.3 Days	CHF 1000	Submit
Healthcare healthcare	2.7	4.7	2013	21.5 Days	CHF 2700	Submit

Preprints.org is a multidisciplinary platform offering a preprint service designed to facilitate the early sharing of your research. It supports and empowers your research journey from the very beginning.

MDPI Topics is collaborating with Preprints.org and has established a direct connection between MDPI journals and the platform. Authors are encouraged to take advantage of this opportunity by posting their preprints at Preprints.org prior to publication:

1. Share your research immediately: disseminate your ideas prior to publication and establish priority for your work.
2. Safeguard your intellectual contribution: Protect your ideas with a time-stamped preprint that serves as proof of your research timeline.
3. Boost visibility and impact: Increase the reach and influence of your research by making it accessible to a global audience.
4. Gain early feedback: Receive valuable input and insights from peers before submitting to a journal.
5. Ensure broad indexing: Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers