Workplace-oriented data processing method and system
By using a stream processing framework and a multi-agent reinforcement learning network, workplace health data is analyzed in real time, solving the problem of uncoordinated multimodal data processing in existing technologies. This enables accurate assessment and dynamic intervention of employee health status, improving the accuracy of health risk prediction and management efficiency.
Patent Information
- Application Number
- CN202511780959.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-28
- Publication Date
- 2026-02-27
AI Technical Summary
Existing technologies struggle to effectively capture contextual dependencies, semantic disambiguation, and subtle sentiment in workplace health data analysis. Furthermore, the lack of collaborative analysis mechanisms in multimodal data processing leads to inaccurate health status assessments and hinders real-time early warning and dynamic intervention.
The system receives and buffers questionnaire and sensor data in real time through a stream processing framework, performs natural language processing and extracts physiological features, calculates cross-modal attention weights using a dynamic semantic alignment layer, combines a temporal prediction model and an occupational health knowledge graph to generate health risk prediction probabilities, and outputs personalized intervention actions through a multi-agent reinforcement learning strategy network.
It enables real-time and accurate assessment and dynamic intervention of workplace employee health risks, improves the accuracy of risk prediction and the level of intelligence in health management, and forms a complete closed loop of perception, decision-making, action and learning.