药品生产安全机器人巡检方法及智能系统
By using multi-source data fusion and adaptive inspection methods, the adaptability and data fusion issues of the drug production safety inspection system were solved, achieving efficient and accurate safety management and closed-loop control, and improving the safety and compliance of drug production.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2025-06-20
- Publication Date
- 2026-07-17
AI Technical Summary
Existing drug production safety inspection systems lack adaptability, data fusion capabilities, forward-looking early warning, and closed-loop feedback, resulting in unreasonable allocation of inspection resources, serious information silos, and passive risk identification, thus failing to achieve efficient and accurate safety management.
A drug production safety robot inspection method using multi-source heterogeneous data fusion is adopted. By acquiring environmental, equipment, vision, and personnel data in real time, a dynamic risk assessment model is constructed to generate adaptive inspection tasks. The mobile inspection terminal is used for precise scheduling, and a multi-modal fusion AI safety hazard identification engine is used for in-depth analysis to form a closed-loop control.
It enables predictive and proactive safety management of the drug production process, improves the dynamic optimization and allocation of inspection resources and the accuracy of hazard identification, reduces the missed detection rate, and enhances the system's self-optimization capabilities and compliance management.
Smart Images
Figure CN120686693B_ABST