Synthesis of decision making in a distributed intelligent personnel health management system on offshore oil platform
This paper proposes a methodological approach for the decision synthesis in a geographically distributed intelligent health management system for oil workers working in offshore industry. The decision-making methodology is based on the concept of a person-centered approach to managing the health and safety of personnel, which implies the inclusion of employees as the main component in the control loop. This paper develops a functional model of the health management system for workers employed on offshore oil platforms and implements it through three phased operations that is monitoring and assessing the health indicators and environmental parameters of each employee, and making decisions. These interacting operations combine the levels of a distributed intelligent health management system. The paper offers the general principles of functioning of a distributed intelligent system for managing the health of workers in the context of structural components and computing platforms. It presents appropriate approaches to the implementation of decision support processes and describes one of the possible methods for evaluating the generated data and making decisions using fuzzy pattern recognition. The models of a fuzzy ideal image and fuzzy real images of the health status of an employee are developed and an algorithm is described for assessing the deviation of generated medical parameters from the norm. The paper also compiles the rules to form the knowledge bases of a distributed intelligent system for remote continuous monitoring. It is assumed that embedding this base into the intelligent system architecture will objectively assess the trends in the health status of workers and make informed decisions to eliminate certain problems
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