1 publication

• Published Subscription Review Article 17 Jan 2026

  Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence

  By Bhargav Chebrolu

  Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …

  Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article →