## 5 Conclusions  
The AGAPE platform, currently in an ongoing pilot involving 112 OAs across three European regions, has demonstrated its potential in advancing active ageing through the use of IoT and wearable technologies. This paper's distinction is in discovering four distinct profiles among OAs that highlight the diverse technological needs and preferences within this demographic. These profiles, ranging from very low to high digital literacy, highlight the necessity of tailoring innovative solutions to individual user profiles for maximum effectiveness. However, the results obtained from the System Usability Scale (SUS) and Technostress assessments indicate areas for improvement. The mean SUS score of 64.65, just below the average usability benchmark of 68, along with a high standard deviation of 16.67, suggests significant variability in the platform's usability among different users. Similarly, the technostress scores, averaging at 16.83 with a standard deviation of 10.64, reveal a range of comfort levels with technology among the participants. These findings highlight the need for ongoing refinement of the AGAPE platform, particularly in enhancing its usability and reducing technostress for users with lower digital literacy. To further enhance the AGAPE framework, several future directions can be pursued; The AGAPE ecosystem should focus on creating a more intuitive and user-friendly interface, with the aim of making technological advancements accessible and beneficial to a broader range of users. Efforts to mitigate Technostress through personalised training and support can also enhance user experience and acceptance. By addressing these areas, the AGAPE solutions have the potential to become an integral tool in the realm of older age care, promoting active ageing and enriching the lives of OA through technology. This study sets the foundation for such advancements, paving the way for more inclusive and effective active ageing solutions. The AGAPE ecosystem can incorporate the HL7 FHIR data standards to seamlessly interface with existing Electronic Health Record systems [49]. This would facilitate the effortless exchange of health data across carers and healthcare providers. The integration would enable a comprehensive approach to patient care, enhancing the ability to provide real-time updates and fostering better coordination among many stakeholders engaged in the care of OAs. The integration of advanced data analytics and artificial intelligence can augment the decision-making capabilities of the AGAPE platform. Forecasting the level of PA in an OA can assist in recognising potential risks and offering timely interventions, hence enhancing health outcomes for senior individuals. In addition, advanced algorithms can be implemented to classify the various PAs performed by the OA. For instance, identify the activities of an individual as either running, walking, or sleeping. By consistently updating and broadening the selection of wearable devices that are compatible with the AGAPE Assistant, OA will be able to stay up-to-date with the most recent technological advancements. For example, utilising a chest-mounted heart rate sensor can result in more precise heart rate measurements compared to a sensor worn on the wrist. Additionally, this will offer enhanced health monitoring functionalities. Engaging in partnerships with local community organisations and influential figures can facilitate the comprehension of the distinct requirements and preferences of various demographic cohorts. This participation can help promote the adoption and acceptance of the AGAPE ecosystem within these communities. For example, the AGAPE ecosystem is currently undergoing testing in three different countries, but we have intentions to expand this testing to additional countries. Conceptualization, J.S.J., I.C. and F.A. ; methodology, J.S.J. ; software, J.S.J., F.A., D.N. and J.L. ; validation, E.T., F.C. and D.K. ; formal analysis, J.S.J. and C.P. ; investigation, I.C., C.P., B.F. and A.P. ; data curation, I.C., C.P. and A.P.