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Model-based Digital Twins of Medicine Dispensers for Healthcare IoT Applications

Hassan Sartaj, Shaukat Ali, Tao Yue, Kjetil Moberg

TL;DR

The paper tackles the challenge of safely testing healthcare IoT applications that involve diverse medical devices by replacing physical medicine dispensers with model-driven digital twins (DTs). It presents a domain- and executable-model-based workflow to construct, operate, and synchronize DTs with real devices, including a DT Communication Server and REST APIs for system-under-test integration. An Oslo City industrial case using the Karie dispenser demonstrates DT fidelity exceeding $92\%$ relative to physical devices and shows scalability to 100 concurrent DTs. The work contributes an open-source implementation and a feasible path toward cost-effective, large-scale, automated testing in healthcare IoT environments. This approach can generalize to other medical devices and supports ongoing evolution of healthcare IoT platforms.

Abstract

Healthcare applications with the Internet of Things (IoT) are often safety-critical, thus, require extensive testing. Such applications are often connected to smart medical devices from various vendors. System-level testing of such applications requires test infrastructures physically integrating medical devices, which is time and monetary-wise expensive. Moreover, applications continuously evolve, e.g., introducing new devices and users and updating software. Nevertheless, a test infrastructure enabling testing with a few devices is insufficient for testing healthcare IoT systems, hence compromising their dependability. In this paper, we propose a model-based approach for the creation and operation of digital twins (DTs) of medicine dispensers as a replacement for physical devices to support the automated testing of IoT applications at scale. We evaluate our approach with an industrial IoT system with medicine dispensers in the context of Oslo City and its industrial partners, providing healthcare services to its residents. We study the fidelity of DTs in terms of their functional similarities with their physical counterparts: medicine dispensers. Results show that the DTs behave more than 92% similar to the physical medicine dispensers, providing a faithful replacement for the dispenser.

Model-based Digital Twins of Medicine Dispensers for Healthcare IoT Applications

TL;DR

The paper tackles the challenge of safely testing healthcare IoT applications that involve diverse medical devices by replacing physical medicine dispensers with model-driven digital twins (DTs). It presents a domain- and executable-model-based workflow to construct, operate, and synchronize DTs with real devices, including a DT Communication Server and REST APIs for system-under-test integration. An Oslo City industrial case using the Karie dispenser demonstrates DT fidelity exceeding relative to physical devices and shows scalability to 100 concurrent DTs. The work contributes an open-source implementation and a feasible path toward cost-effective, large-scale, automated testing in healthcare IoT environments. This approach can generalize to other medical devices and supports ongoing evolution of healthcare IoT platforms.

Abstract

Healthcare applications with the Internet of Things (IoT) are often safety-critical, thus, require extensive testing. Such applications are often connected to smart medical devices from various vendors. System-level testing of such applications requires test infrastructures physically integrating medical devices, which is time and monetary-wise expensive. Moreover, applications continuously evolve, e.g., introducing new devices and users and updating software. Nevertheless, a test infrastructure enabling testing with a few devices is insufficient for testing healthcare IoT systems, hence compromising their dependability. In this paper, we propose a model-based approach for the creation and operation of digital twins (DTs) of medicine dispensers as a replacement for physical devices to support the automated testing of IoT applications at scale. We evaluate our approach with an industrial IoT system with medicine dispensers in the context of Oslo City and its industrial partners, providing healthcare services to its residents. We study the fidelity of DTs in terms of their functional similarities with their physical counterparts: medicine dispensers. Results show that the DTs behave more than 92% similar to the physical medicine dispensers, providing a faithful replacement for the dispenser.
Paper Structure (32 sections, 9 figures, 3 tables)

This paper contains 32 sections, 9 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Application Context
  3. Real-World Application
  4. Industrial Context and Challenges
  5. Model-based DT Creation and Operation
  6. Constructing DT Structure
  7. Domain Model of Medicine Dispensers
  8. Generating Instance Model
  9. Constructing DT Behavior
  10. Operating DT
  11. Generating APIs
  12. Enabling Communication
  13. Synchronizing DTs with Physical Devices
  14. Evaluation
  15. Implementation
  16. ...and 17 more sections

Figures (9)

  • Figure 1: Context: an IoT-based healthcare system
  • Figure 2: An outlook of our approach, including required inputs, its core components, integration with smart medicine dispenser devices, and testing components. The arrow () shows information flow, () shows two-way communication, () depicts a mapping, and () represents communications with different medicine dispensers.
  • Figure 3: A domain model for smart medicine dispenser devices
  • Figure 4: (Left) A state machine of a medicine dispenser - (Right) A code snippet for state Dispense
  • Figure 5: An example of Model-DT-Device mapping
  • ...and 4 more figures