Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly.

Healthcare systems across Europe and globally are increasingly challenged by the need to deliver high‐quality, coordinated care for complex patient populations, such as those living with chronic heart failure (CHF). Many national healthcare policies consider the adoption and implementation of patient‐centred and interoperable information communication technologies‐enabled solutions offered in a single digital platform as a key facilitator towards the transition to integrated and coordinated care. Aiming to support CHF patients and to assist their management, in this paper, we present CareCardia, a modular digital solution designed to support the comprehensive management of CHF. CareCardia offers an interoperable ecosystem that connects healthcare professionals, informal caregivers and patients along a unified CHF care pathway spanning across diagnosis, acute care and jointly managed long‐term care. Specifically, CareCardia integrates state‐of‐the‐art, clinical evidence‐based technologies such as a clinical decision support system and an exergaming platform that will follow patients through the CHF journey. This paper outlines the system architecture and core functionalities of CareCardia prototype. We also present early findings from the initial exploration of the tool, discussing its anticipated impact on CHF and its potential to foster patient empowerment across the continuum of care.

Background/Objectives: Remote patient monitoring (RPM) is recognized as a key component of health system transformation in Europe, in the context of vulnerable populations. However, its large-scale adoption remains uneven across countries. The research explored how technical infrastructure, governance and regulation, interoperability, and ecosystem readiness influence RPM adoption and scale-up in seven European country contexts. Methods: An exploratory qualitative cross-country study combined targeted desk research with semi-structured interviews conducted between February and March 2025. The interviews were recorded with consent, manually transcribed, anonymized, and analyzed using a manual hybrid deductive–inductive thematic approach. The desk research provided contextual information and remained distinct from the interview-derived findings. Results: The analysis was organized around four higher-order themes including digital infrastructure and RPM technologies; governance and regulatory frameworks; interoperability and health-data integration; implementation barriers and ecosystem readiness. RPM technologies were present in all examined contexts, but their integration into routine care remained uneven. Recurrent barriers included fragmented reimbursement pathways, uneven operationalization of EU rules, limited interoperability, weak integration with Electronic Health Records and clinical workflows, digital-literacy gaps, and insufficient mechanisms for progressing from pilots to sustained implementation. Conclusions: Stakeholders more frequently identified system-level implementation conditions, including governance, reimbursement, interoperability, and workforce readiness, than technology availability alone as barriers to RPM scale-up. The European Health Data Space may provide an enabling framework, but its impact will depend on national and regional implementation capacity.