This study introduces a robust and cost-effective acoustic-based high-energy impulse sound detection and localization system. The system utilizes state-of-the-art (SOTA) multi-channel signal processing, spatial filtering, and machine learning techniques, enabling it to detect and localize high-energy impulse sound sources in urban environments. Sponsored by Heavy Industries Taxila, the proposed system has the following specifications:
- 1 second response time
- 360° × 180° surveillance
- Directional accuracy: ±10°
- Detection probability: up to 90%
- Closest point of approach: 200 meters
- Fully automated operation