Abstract—By the year 2030, more than one in six people worldwide will be 60 years old or above. This elderly population is projected to grow to approximately 2.1 billion individuals by mid-century. This demographic shift presents significant challenges and opportunities for healthcare systems worldwide. Ageing in place, which enables older adults to remain safely and independently in their homes, is increasingly recognized as a cost-effective and quality-enhancing alternative to institutional care. However, its success hinges on intelligent, adaptive technologies that support personalized healthcare delivery. Despite advances in Artificial Intelligence (AI), machine learning, and digital health, current systems often rely on generic, one-size-fits-all solutions that fail to address the complex, individualized needs of ageing populations. This paper presents a comprehensive literature review examining the use of personalized assistive healthcare technologies and behavioral data in aging-in-place settings. It reveals key gaps, including poor adaptability to individual needs, limited integration of real-time data, and a lack of long-term evidence from real-world deployments. Challenges such as usability, ethical concerns, and insufficient system interoperability further limit effectiveness. To address these issues, we argue for a paradigm shift toward person-centered, adaptive systems that evolve with users over time. We outline the need for hybrid monitoring approaches, scalable personalization frameworks, and inclusive design strategies to ensure sustainable and impactful solutions for ageing populations globally.
 
Keywords—ageing-in-place, personalization, assistive technologies, older adults


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