Ultracapacitor management system for IoT-based streetlight application
Bibliographic record
Abstract
This paper proposes the highly efficient ultracapacitor management system (UCMS) for IoT-enabled, solar-powered streetlights. Existing battery-based storage solutions for streetlighting suffer from limited cycle life, slow recharge rates, and high maintenance overhead, motivating the need for a more durable and responsive approach. The proposed UCMS optimizes ultracapacitor (UC) charging and discharging cycles, improving streetlight efficiency and lifespan. The internet-of-things (IoT) integration allows for real-time monitoring and control. The system performance is evaluated through simulation, certification testing, and real-world deployment. Key features of hardware and software design include the ability to charge UCs at a minimum current of 0.5 A and a fault-tolerant design for enhanced reliability. The UCMS demonstrated monitoring accuracy of ≤0.2 V for voltage and ≤ 0.1 A for current, with successful wireless control and data acquisition. Design considerations and insights for broader UC-based energy storage applications are also discussed in this paper.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".