Wearables and the Internet of Things (IoT), Applications, Opportunities, and Challenges: A Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Smart wearables collect and analyze data, and in some scenarios make a smart decision and provide a response to the user and are finding more and more applications in our daily life. In this paper, we comprehensively survey the most recent and important research works conducted in the area of wearable Internet of Things (IoT) and classify the wearables into four major clusters: (i) health, (ii) sports and daily activity, (iii) tracking and localization, and (iv) safety. The fundamental differences of the algorithms associated within each cluster are grouped and analyzed and the research challenges and open issues in each cluster are discussed. This survey reveals that although Cellular IoT (CIoT) has many advantages and can bring enormous applications to IoT wearables, it has been rarely studied by the researchers. This article also addresses the opportunities and challenges related to implementing CIoT-enabled wearables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it