Current demographic trends suggest that people are living longer, while
the ageing process entails many necessities, calling for care services tailored to
the individual senior’s needs and life style. Personalized provision of care
services usually involves a number of stakeholders, including relatives, friends,
caregivers, professional assistance organizations, enterprises, and other support
entities. Traditional Information and Communication Technology based care and
assistance services for the elderly have been mainly focused on the development
of isolated and generic services, considering a single service provider, and
excessively featuring a techno-centric approach.
In contrast, advances on collaborative networks for elderly care suggest the
integration of services from multiple providers, encouraging collaboration as a
way to provide better personalized services. This approach requires a support
system to manage the personalization process and allow ranking the {service,
provider} pairs.
An additional issue is the problem of service evolution, as individual’s care
needs are not static over time. Consequently, the care services need to evolve
accordingly to keep the elderly’s requirements satisfied. In accordance with these
requirements, an Elderly Care Ecosystem (ECE) framework, a Service
Composition and Personalization Environment (SCoPE), and a Service Evolution
Environment (SEvol) are proposed.
The ECE framework provides the context for the personalization and
evolution methods. The SCoPE method is based on the match between the
customer´s profile and the available {service, provider} pairs to identify suitable
services and corresponding providers to attend the needs. SEvol is a method to build an adaptive and evolutionary system based on the MAPE-K methodology
supporting the solution evolution to cope with the elderly's new life stages.
To demonstrate the feasibility, utility and applicability of SCoPE and SEvol,
a number of methods and algorithms are presented, and illustrative scenarios are
introduced in which {service, provider} pairs are ranked based on a
multidimensional assessment method. Composition strategies are based on
customer’s profile and requirements, and the evolutionary solution is
determined considering customer’s inputs and evolution plans.
For the ECE evaluation process the following steps are adopted: (i) feature
selection and software prototype development; (ii) detailing the ECE framework
validation based on applicability and utility parameters; (iii) development of a
case study illustrating a typical scenario involving an elderly and her care needs;
and (iv) performing a survey based on a modified version of the technology
acceptance model (TAM), considering three contexts: Technological,
Organizational and Collaborative environment
