Development of Smart Footwear for Sustainable Energy Harvesting
Bibliographic record
Abstract
This study presents a novel method for energy harvesting in wearable devices through the development of smart footwear that generates and monitors sustainable energy from human motion.The system integrates piezoelectric sensors, a microcontroller, a rechargeable battery, and a boost converter.Mechanical vibrations from walking are captured by sensors in the sole and converted into electrical energy, which is stored in the battery.A monitoring system embedded in the ankle brace tracks real-time energy generation and consumption.Experimental results indicate that the footwear produces sufficient power for low-energy applications, with energy output directly proportional to foot traffic.The mechanical-to-electrical conversion efficiency is 4.44%, and the monitoring system operates at 0.716 W. The battery charges from 3.6 V to 4.2 V in approximately 2.7 hours, with a recommended charging limit of 90% to extend the battery lifespan.This design promotes sustainable energy use in wearables and offers a practical foundation for optimizing energy harvesting in future technologies.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".