1. Proceedings
  2. I3M
  3. 2020
  4. IWISH
  5. 10.46354/i3m.2020.iwish.014

Application-based IoT-system for pandemic prevention based on platform-approach

  • a Volkhard Klinger , 
  • b Sebastian Bohlmann
  • a,b Department of Embedded Systems, University of Applied Science Hannover (FHDW), D-30173 Hannover, LS, Germany
Cite as
Klinger V., Bohlmann S. (2020). Application-based IoT-system for pandemic prevention based on platform-approach. Proceedings of the 9th International Workshop on Innovative Simulation for Healthcare (IWISH 2020), pp. 77-85. DOI: https://doi.org/10.46354/i3m.2020.iwish.014

Abstract

For the quantitative description and prognosis of pandemic propagation processes, simulations and methods of theoretical biology, such as the SIR model (susceptible-infected-removed model), are used. Important in all these methods are models and data. These describe cause-and-effect relationships on the basis of which the models can be developed and improved. However, data collection and data correlation in particular are costly and often complicated against the background of data protection. Within the framework of a project on electroneurogram (ENG)-based prosthesis control, work is already underway on a data-based system identification for model generation; in this context, a hardware-/software-platform has been developed that also has a Internet of Things (IoT) extension and can be used for the required sensor fusion. These methods can be used within the existing framework. The flexibility of the platform is also demonstrated. Part of the platform are not only new approaches to modelling based on agent-based evolutionary methods, but also a concept that transparently secures personal rights in different modes of operation. The aim is not only to further investigate microscopic relationships of the pandemic, but to evaluate in particular macroscopic relationships within a set of scenarios, i.e. to establish cause-and-effect relationships more precisely between different symptoms and an infection.

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