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Numrering	Referens	Omslagsbild	Hitta
1.	Gil, Eric Bernd, et al. (författare) Body Sensor Network: A Self-Adaptive System Exemplar in the Healthcare Domain 2021 Ingår i: 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). - 2157-2321. - 9781665402897 Konferensbidrag (refereegranskat)abstract 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

Gil, Eric Bernd, et al. (författare)
Body Sensor Network: A Self-Adaptive System Exemplar in the Healthcare Domain
2021
Ingår i: 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). - 2157-2321. - 9781665402897
Konferensbidrag (refereegranskat)abstract
- 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

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