Support vector machine and edge computing enhanced real-time ambulance siren detection system
Yazarlar (2)
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY |
| Dergi ISSN | 1300-1884 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | |
| Dergi Grubu | Q3 |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2025 |
| Cilt No | 40 |
| Sayı | 2 |
| Sayfalar | 1147 / 1158 |
| Özet |
| This research details the development and implementation of an edge computing and Polynomial Support Vector Machine (SVM)-based sound classification model for effective detection of ambulance sirens and general traffic noises within Turkey's traffic management infrastructure. Utilizing advanced algorithms and innovative techniques, the model demonstrates significant success in differentiating sounds in a traffic environment. Uniform Manifold Approximation and Projection (UMAP) and Principal Component Analysis (PCA) demonstrate the model's ability to effectively process high-dimensional data into low-dimensional spaces, allowing for clear distinction between classes. The study presents an integrated sound classification system with edge computing technology, highlighting its potential to provide real-time solutions for traffic management. This technology significantly contributes to rapid and accurate ... |
| Anahtar Kelimeler |
