Publications / CCC 2025 - Zadar, Croatia
Construction sites are inherently hazardous environments where accidents and fatalities constitute a significant global concern. Despite continuous efforts to enhance safety, the incidence of workplace accidents within the construction industry remains elevated. This study introduces HUST AI Box, an AI and computer vision-based safety management system, enhanced by the integration of DeepSeek, a large language model (LLM), to provide advanced natural language processing (NLP) capabilities for real-time decision support, knowledge management, and safety optimization. The integration of DeepSeek enables the system to process unstructured text data and provide actionable insights, significantly enhancing the safety management framework. We demonstrate the localized deployment of DeepSeek within the HUST AI Box system, ensuring robust performance and real-time responsiveness in dynamic construction environments. The results suggest that the combined system significantly enhances safety management by automating the detection of unsafe behaviours, improving the efficiency and precision of face recognition, and leveraging DeepSeek for real-time decision support and knowledge management. This system is versatile and can be applied in various other contexts beyond construction sites.