Ambulance Siren Detection using Artificial Intelligence in Urban Scenarios
Traffic density is growing day by day due to the increasing population and affordable prices of cars. It created a void for traffic management systems to cope with traffic congestion and prioritize ambulances. The consequences can be a terrible situation. Emergency vehicles are the most affected in...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sir Syed University of Engineering and Technology, Karachi.
2022-06-01
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| Series: | Sir Syed University Research Journal of Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sirsyeduniversity.edu.pk/ssurj/rj/index.php/ssurj/article/view/467 |
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| Summary: | Traffic density is growing day by day due to the increasing population and affordable prices of cars. It created a void for traffic management systems to cope with traffic congestion and prioritize ambulances. The consequences can be a terrible situation. Emergency vehicles are the most affected in these situations, and inadequate traffic control can put many lives at stake. Ambulances on the road are detected using an acoustic-based Artificial Intelligence system in this article. Emergency vehicle siren and road noise datasets have been developed for ambulance acoustic monitoring. The dataset is developed along with a deep learning (MLP-based) model and trained to use audio monitoring to predict the ambulance presence on the roads. This model achieved 90% accuracy when trained and validated against a developed dataset of only 300 files. With this validated algorithm, researchers can develop a real-time hardware-based model to detect emergency vehicles and make them arrive at the hospital as soon as possible.
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| ISSN: | 1997-0641 2415-2048 |