The global demographic shift toward an aging population presents a critical socio-economic challenge, necessitating "aging in place" solutions that balance autonomy with safety. Although the Internet of Medical Things (IoMT) offers a theoretical foundation for remote monitoring, current implementations often fail to meet real-world requirements due to high costs, intrusive sensing modalities, and a lack of contextual reasoning. This article outlines the architectural requirements of the next-generation platform for digital health support. We argue that the future of monitoring the elderly lies within the framework of Agentic Artificial Intelligence (AI), a system that not only records events but also reasons about them, detects and adapts to anomalies, and communicates with caregivers through natural language. As a result, the next generation of digital wellness platforms must bridge the gap between technical data and human understanding, providing high-precision detection, human-readable, and context-aware recommendations. This shifts systems from simple data loggers to proactive decision-supporting tools.

COVID-19 had substantial effects on the IoT community which designs systems for safety: the urge to face masks worn by everyone, the analysis of crowds to avoid the spread of the disease, and the sanitization of public environments has led to exceptional research acceleration and fast engineering of the related solutions. Now that the pandemic is losing power, some applications are becoming less important, while others are proving to be useful regardless of the criticality of COVID-19. The Safe Place project is a prime example of this situation (DATE23 MPP category: final stage). Safe Place is an Italian 3M euro regional industrial/academic project, financed by European funds, created to ensure a multidisciplinary choral reaction to COVID-19 in critical environments such as rest homes and public places. Safe Place consortium was able to understand what is no longer useful in this post-pandemic period, and what instead is potentially attractive for the market. For example, the detection of face masks has little importance, while sanitization does have much. This paper shares such analysis, which emerged through a co-design process of three public Safe Place project demonstrators, involving heterogeneous figures spanning from scientists to lawyers.