Smoke and camera tampering detection system based on single-board computer for real-time fire monitoring
Keywords:
smoke detection, computer vision, video surveillance systems, single-board computerAbstract
An edge-based architecture for a video surveillance system with integrated smoke and camera tampering detection is presented. The system consists of parallel-executing modules responsible for configuration management and video data processing, including receive, analysis, and transmission. Smoke detection is performed using computer vision algorithms based on the sequential extraction of discriminative visual features: motion direction, colour characteristics, and impact on background visibility. Camera tampering is detected by evaluating scene sharpness through an edge-detection filter. High-resolution video processing is performed on a single-board computer, with computational tasks distributed across the cores of a multi-core central processor to optimise performance. The proposed approach significantly reduces the load on the central node of the surveillance infrastructure, which is a critical advantage for scalable deployments involving numerous cameras. Experimental results demonstrate high detection accuracy for smoke and tampering, as well as stable real-time operation of the implemented architecture.
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