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Smart home for enhanced healthcare: exploring human machine interface oriented digital twin model

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Abstract

Digital twin (DT) and other emerging technologies such as the Internet of Things (IoT), data mining, reinforcement learning, remote intelligent control, and machine learning offer enormous potential for transforming today’s equipment model into intelligent devices. It is one of the key technologies to endorse the virtual and remote intelligent control system for home-devices (HD) in human comfort (disabled/elderly). The relevant research is in the initial stage, and how to realize the DT of home-equipment control has become a vital problem to be solved. This study expounds on the suggestion and application of the DT model and summarizes the research and application progress from the aspect of the home-devices’ DT (HDDT) modeling. This modelling approach is three-staged: in terms of physical entities, virtual entities, and connectivity (data communication). The proposed model utilizes an interactive mechanism for the intelligent control of HD, by integrating DT and virtual simulation technologies to establish a human cyber-physical system (HCPS), specifically addressing the challenges associated with remote-control problems. The HCPS aims to achieve a deep integration and interface between the physical and virtual spaces of smart-device information. Using the game theory approach to create multi-physical entities and DT entities of IoT-based HD like washing machines, lamps, breakers, heaters, kitchen equipment, TV, AC, etc. The next step is to develop high-performance smart devices and build a reasonable sensing network to improve the depth and range of connection. The equipment tracking test showed that the system could control virtual reality synchronization, positional accuracy, and quality control for smart-devices development in HDDT modeling.

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Authors and Affiliations

  1. Hubei Key Laboratory of Advanced Technology for Automotive Components, School of Automotive Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Muhammad Usman Shoukat, Lirong Yan, Jiawen Zhang & Yu Cheng

  2. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China

    Muhammad Umair Raza

  3. College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan, 030024, China

    Ashfaq Niaz

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  1. Muhammad Usman Shoukat
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  2. Lirong Yan
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  3. Jiawen Zhang
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  4. Yu Cheng
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  5. Muhammad Umair Raza
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Correspondence to Lirong Yan.

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Shoukat, M.U., Yan, L., Zhang, J. et al. Smart home for enhanced healthcare: exploring human machine interface oriented digital twin model. Multimed Tools Appl 83, 31297–31315 (2024). https://doi.org/10.1007/s11042-023-16875-9

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  • DOI: https://doi.org/10.1007/s11042-023-16875-9

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