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.
翻译:最近的世界性事件揭示了保健领域以人为中心的系统工程的需要。这些系统必须准备迅速而安全地发展,要符合未经预测的环境和无情扩散的不断变化的病原体。这种情景扼杀医院的基础设施,使没有准备在没有费用高昂的再造的情况下处理以人为中心的环境的保健系统瘫痪。面对这些挑战,我们提供SA-BSN -- -- 自我开发身体传感器网络 -- -- 原型,以探索相当动态的病人健康状况监测。示范系统侧重于自我适应,并出现阻碍每次执行后系统可靠性和电池消耗之间相互作用的情景。此外,我们还提供:(一) 噪音注射机制,(二) 基于档案的病人配置,(三) 六种保健传感器模拟,和(四) 自我改造的可扩展/可再使用的控制器。工艺品在ROS(Robot操作系统)中实施,它包含了方便使用和依赖活跃开放源社区支持等原则。