Construction sites increasingly rely on computer vision systems to monitor safety protocols, specifically for detecting personnel and the presence of personal protective equipment. These systems utilize models such as YOLO and DETR, which are fine-tuned using real-world construction data to improve detection accuracy.
The deployment strategy requires careful planning regarding camera placement and density. While a single wide-angle camera can cover a large area, it often lacks the resolution needed for detailed inspections. Industry standards typically suggest installing approximately 15 cameras per residential complex to ensure adequate coverage and detail.
Environmental factors like low light, dust, and rain significantly influence system performance. Developers emphasize that neural networks cannot compensate for poor physical visibility. Consequently, system testing must account for these varying conditions rather than relying on generalized accuracy metrics.
Data processing can occur via cloud infrastructure, local customer servers, or edge devices located directly on the site. The latency of alerts sent to site managers depends on the entire technical chain, including network connectivity and processing speed, which are evaluated during the implementation phase.
