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Body Sensor Network: A Self-Adaptive System Exemplar in the Healthcare Domain

机译:身体传感器网络:医疗域中的自适应系统示例

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Recent worldwide events shed light on the need of human-centered systems engineering in the healthcare domain. These systems must be prepared to evolve quickly but safely, according to unpredicted environments and ever-changing pathogens that spread ruthlessly. Such scenarios suffocate hospitals' infrastructure and disable healthcare systems that are not prepared to deal with unpredicted environments without costly re-engineering. In the face of these challenges, we offer the SA-BSN - Self-Adaptive Body Sensor Network - prototype to explore the rather dynamic patient's health status monitoring. The exemplar is focused on self-adaptation and comes with scenarios that hinder an interplay between system reliability and battery consumption that is available after each execution. Also, we provide: (i) a noise injection mechanism, (ii) file-based patient profiles' configuration, (iii) six healthcare sensor simulations, and (iv) an extensible/reusable controller implementation for self-adaptation. The artifact is implemented in ROS (Robot Operating System), which embraces principles such as ease of use and relies on an active open source community support.
机译:最近的全球活动揭示了在医疗领域的以人为本的系统工程需求。根据未预测的环境和不断变化的病原体,必须准备好这些系统快速但安全地进化,但不断变化的病原体。这种方案窒息了医院的基础设施和禁用医疗保健系统,这些系统不准备处理未预测的环境,而无需昂贵重新设计。面对这些挑战,我们提供SA-BSN - 自适应身体传感器网络 - 原型,用于探索相当动态的患者的健康状况监控。该示例专注于自适应,并且随着在每次执行之后可用的系统可靠性和电池消耗之间的相互作用而来的场景。此外,我们提供:(i)噪声注入机制,(ii)基于文件的患者配置文件配置,(iii)六个医疗保健传感器模拟,(iv)用于自适应的可扩展/可重复使用的控制器实现。伪像在ROS(机器人操作系统)中实现,其包括易于使用的原理,并依赖于主动开源社区支持。

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