## 6 Discussions of Workshop Results
### WISE-WARE: Intelligent Middleware  
The proliferation of advanced robotic systems and Internet of Things (IoT) devices presents unprecedented opportunities to enhance the quality of life for individuals living with frailty. However, the full potential of these technologies in creating a truly'smart and assistive' home environment remains largely unrealised. Based on our research findings, we introduce WISE-WARE, an innovative intelligent middleware framework designed to address the current fragmentation of COTS assistive devices. By creating such a middleware, we aim to (1) synthesise data from connected devices to automate and augment residents' daily activities, and (2) facilitate the secure sharing of anonymised data to foster the development of evidence-based solutions. By seamlessly integrating diverse assistive technologies and leveraging previously untapped data streams, WISE-WARE serves as a crucial catalyst for cutting-edge research and applied robotics. This integrative approach enables precise identification of support needs, facilitates targeted interventions, and provides profound insights to inform the development of personalised, next-generation home support systems. We applied the MoSCoW prioritisation method as a part of our semi-structured interviews to ensure that our development efforts were tightly aligned with user needs and project constraints, allowing us to create a minimum viable product that delivers immediate value to People living with Frailty while maintaining a clear roadmap for future enhancements. The application of the MoSCoW method in the development of WISE-WARE proved invaluable for our co-design approach. By categorising features into _Must have_, _Should have_, _Could have_, and _Won't have_, we established a clear hierarchy of priorities that guided our development process. As shown in Table 5, there is a strong emphasis on user-centred design, accessibility, and adaptability. The _Must-haves_ (M1 and M2) prioritise usability and independence, ensuring that users can learn at their own pace and troubleshoot problems easily. The _Should-haves_ (S1, S2, and S3) focus on flexibility, user control, and adaptability, highlighting the importance of accommodating individual needs and preferences. The _Could-haves_ (C1 and C2) introduce advanced features that could enhance the user experience, such as personalised tutoring and integrated assistance from multiple devices. Notably, the _Won't-have_ (W1) requirement indicates that WISE-WARE design and implementation should not focus on developing various control modalities as user faculties deteriorate at this current stage, emphasising the need for a simple and intuitive interface. Building on these recommendations, we designed our intelligent middleware based on the open-source FIWARE v.8.6 architecture to enable standardised and interoperable intelligent solutions, shown in Figure 14. This approach allowed us to integrate proprietary 3 rd-party robotic and assistive technology services and expose their functionalities using technologies similar to FIWARE next-generation service interfaces (NCSI) API. This approach not only enhances the flexibility and scalability of WISE-WARE but also fosters a collaborative ecosystem, where diverse stakeholders can contribute to the development of innovative, user-centred solutions for individuals living with frailty. The FIWARE-based design of WISE-WARE enables seamless integration of a diverse array of robotics and assistive technology devices, as well as other services, allowing for streamlined processing and consumption by various AI, operational, business, and data analytics applications. Furthermore, this architecture facilitates the integration of the home environment with other smart solutions and systems at different geographical levels, fostering a holistic and interconnected ecosystem.