Conversion of Roadway Noise to Electrical Energy: An Innovative Approach for Sustainable Energy Generation
Bibliographic record
Abstract
Roadway noise is the collective sound energy emanating from motor vehicles.It consists chiefly on road surfaces, tire, engine/transmission, aerodynamic, and braking elements.Noise of rolling tires driving on pavement is found to be the biggest contributor of highway noise and increases with higher vehicle speeds.This study explores the use of a rather unconventional form of energy (Sound).An application is proposed for the same in which a distinctly designed circuitry is used to convert the sound produced by a loudspeaker.Based on the law of electromagnetic induction, the vibrations produced by the speaker can be converted into electrical energy.The use of sound energy is both clean and unconventional.It is an entire paradigm shift from the concept of noise cancellation to a new idea of noise utilization.This paper takes a step forward in this direction, using sound as a source of energy to provide a viable electronic source in a vehicle, converting the sound waves into electrical energy indicator used to power streetlight.The result of this study shows the relationship between the spring displacement and the DC voltage generated, and the relationship between the sound source and the generated voltage.It follows that the relationship is directly proportional, and a 95 dB sound generated of 1.3V, which is regulated by using an XL4016 8A regulator to maintain a constant voltage of 2V required to lighten the LED indicator used to power the prototype streetlight implemented in this study.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".