Design and prototyping of low‐power wide area networks for critical infrastructure 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
Low‐energy critical infrastructure monitoring (LECIM) networks is essential for the monitoring of infrastructure facilities in smart cities. One critical requirement of an LECIM network is its wide coverage of up to several kilometres by using a star topology instead of the tree or mesh networks. In meeting this requirement, this study develops a system with a transceiver of extremely high receiver sensitivity based on the IEEE 802.15.4k physical layer specifications. To reduce the energy consumption, the modulation schemes suitable for low complexity detection are chosen for the data transmission in the design. Also, an efficient parallel preamble and payload data detection are adopted at the access point of the proposed LECIM to acquire concurrent packets from respective nodes. Meanwhile, a data‐aided dynamic timing adjustment scheme is proposed for data field detection to rapidly and adaptively synchronise to the long duration of data packet. Furthermore, a testbed is implemented using a software‐defined radio to demonstrate the effectiveness of the proposed system design.
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 | 0.000 | 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