Feasibility and Efficiency of Raspberry Pi as the Single Board Computer Sensor Node
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
Low rate, low power utilization, and ease correspondence are one of the key focuses for the improvement of a practical and effective Sensor Network (SN) framework. This paper introduces this type of cost-effective and efficient sensor system with MFRC522 as sensors and Raspberry Pi as sensor nodes. Raspberry Pi brings the upsides of a Personal Computer (PC) to the space of SNs. This trademark makes it the ideal stage for interfacing with the wide assortment of outer peripherals as appeared in this research work. An efficient customized configuration process for both MFRC522 sensor and Raspberry Pi has been presented in this work in details. Other than this, a comparison of the key components and performances of Raspberry Pi with a portion of the current existing remote sensor nodes is also been presented in this work. This comparison demonstrates that regardless of few drawbacks, the Raspberry Pi remains an economical PC with its effective use in SN space and assorted scope of research applications.
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