16.04.26 (inclusive)
The project is funded as part of the fulfillment of obligations by subsurface users to allocate 1% for R&D in accordance with the rules for the examination of PIT ACF projects. (To participate, the Performer must be a member of the IC "PIT". The application requires the Contractor to provide additional documents)
Finished product
Tasks of subsurface users
Extraction and processing of solid minerals
Labor protection, industrial safety, environmental protection and production operations
Software/ IS,
Mobile app
The lack of best practices for improving the quality of employee health diagnostics using automation of pre-shift medical examinations, comparing data in a single system on completed briefings and subsequent issuance of permits and/or assignments using a single interface, which should result in a reduction in occupational safety incidents.
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Purpose and description of task (project)
Development and implementation of new scientifically based methods and algorithms using advanced artificial intelligence technologies to automatically assess the condition of staff before starting a shift based on the analysis of biomedical monitoring data and the employee's digital profile to: • Ensure a transparent, anti-fraud and automated medical examination process. • Preventing unacceptable work assignments based on objective medical and behavioral data. • Reducing the risks of occupational injuries and deaths from cardiac and other acute conditions. • Reducing the time required for medical examinations and registration of orders. • Implementation of advanced artificial intelligence technologies based on generative LLM models with RAG architecture, decision-making systems based on AI agents, and predictive analytics based on machine learning (ML).
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