SENSOR GRID ARCHITECTURE FOR REMOTE PATIENT HEALTH CARE MONITORING
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
Recent advancement in wireless sensor network technology has completely changed the way the physicians and other health professionals monitor and access patients' health status records in real time, interact with each other, and access the past and present medical records of patients. However, the sensor nodes used in a wireless sensor network to monitor patients' health are resource constraint in nature with limited processing and communication capability. In future, an increase of wireless sensor networks to monitor and analyze patients' health records is envisioned and therefore, the resource constraint nature of wireless sensor networks needs to be addressed. In this paper, an architecture to overcome the limitations of wireless sensor networks is introduced using Grid computing technology. Sensor Grid technology combines these two technologies by extending the Grid computing paradigm to the sensor resources in wireless sensor networks. This paper outlines how the Sensor Grid technology provides a solution for remote patient monitoring to address the resource constraint nature of the sensor devices in a wireless sensor network.
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 | 0.000 | 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