Reference architectures for ambient assisted living: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: For the first time in human history, the number of older people will be higher than the number of children. The prevalence of chronic diseases, such as hypertension, cardiovascular disease, diabetes and mental disorders in older adults is high. Given that, it is essential to make usage of related technology to provide improved health conditions and reduce the costs for promoting ageing in place, and that is precisely the aim of Ambient Assisted Living technology. Considering that these systems provide significant benefit to a vast number of stakeholders, can be applied to the functional diversity of application domains and have high economic and social impacts, it is essential to create reusable and interoperable platforms and standards that are able to deal with the heterogeneity of applications and domains. In this sense, reference architectures have been proposed and evaluated. A comprehensive scoping review concerning the reference architectures must clarify specific aspects, such as what the main domains are and how the solutions effectively deal with them. METHODS: This scoping review will follow the methodology framework defined in 'Scoping studies: advancing the methodology'. In this methodological framework, six stages are proposed for scoping review studies: identifying the research question; identifying relevant studies; study selection; charting the data; collating, summarising and reporting the results; and consultation. The research questions aim to investigate what are the motivations, stakeholders, benefits, domains, approaches, architectural components and governance aspects of the proposed reference architectures and models. The team will focus on the Scopus Document Search, PubMed (MEDLINE), IEEE Xplore Digital Library, ACM Digital Library and Science Direct electronic research databases. The search query is a combination of terms related to Ambient Assisted Living AND Reference Architecture. ETHICS AND DISSEMINATION: This is a scoping review study and there is no requirement for ethical approval, as primary data will not be collected. The results from this scoping review will be published in a peer-reviewed journal and reported at scientific meetings. We intend to share the results with the International Standards and Conformity Assessment - SyC AAL from Canada to use the review as a basis for establishing an assessment model of reference architectures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.133 | 0.145 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.030 | 0.023 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".