Optimal service resource management strategy for IoT-based health information system considering value co-creation of users

TL;DR

This paper develops an adaptive deep reinforcement learning-based strategy for optimal resource management in IoT health information systems, emphasizing user engagement and value co-creation.

Contribution

It introduces a novel deep reinforcement learning approach integrated with a value co-creation model for IoT health services.

Findings

The proposed algorithm improves resource allocation efficiency.

User engagement significantly impacts service performance.

Simulation results validate the effectiveness of the strategy.

Abstract

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service. An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.