A deep learning-based system integrating video, audio, and environmental sensors (temperature/gas concentration) to simulate human multisensory cognition, enabling autonomous hazard identification and predictive decision-making in chemical industry scenarios.

• Cross-Modal Data Fusion:

Synchronizes video, audio, thermal, and gas analytics, transcending single-modality constraints of traditional vision systems.

• Context-Aware Risk Mitigation:

Detects PPE non-compliance (e.g., missing helmets/uniforms) with environmental context analysis (wind/temperature), triggering tiered alerts based on ISO 31000 risk matrices.

• Operational Efficiency Engine:

Achieves 90% reduction in manual inspection efforts through automated defect retrieval.

Enables <50ms incident response and 5-year data traceability via temporal-spatial indexing.