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Simulation-Based Optimization for IoT-Enabled Epidemic Patients Care Systems

Bisheh Niasar, Mohammad Amir | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58061 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Hassan Nayebi, Erfan
  7. Abstract:
  8. This research focuses on examining and improving healthcare systems, particularly during crises and pandemics. Following disasters such as natural calamities and pandemics like COVID-19, healthcare systems face significant challenges due to the increased demand for medical services, creating a substantial threat to the population in the affected regions. This study emphasizes the importance of utilizing modern technologies such as the Internet of Things (IoT) and telemedicine systems in alleviating the pressure on healthcare systems. A combined approach of prediction and multi-objective optimization based on simulation is proposed in this study to improve resource allocation and demand management during crises. This approach provides a framework for selecting and implementing accurate predictions, simulating patient pathways by extracting patterns, and subsequently optimizing the allocation of healthcare resources with multiple objectives. The objectives of this approach include minimizing rejected medical demand and minimizing the cost of adding the required capacity, considering the value or cost of each unit of capacity. This research, using a COVID-19 case study, compares the policies of using modern technologies to improve healthcare systems and reduce the detrimental effects of the disease with traditional treatment policies. In addition, this study, beyond proposing a telemedicine monitoring model, addresses cost estimation and comparison with other traditional healthcare sectors. The results indicate that the daily cost of using telemedicine is significantly lower than the daily cost of other healthcare sectors. Furthermore, the use of IoT equipment in healthcare systems has a significant impact on the optimal management of demand during crises
  9. Keywords:
  10. Simulation Optimization ; Internet of Things ; Demand Forecasting ; Epidemic ; Multiobjective Optimization ; Time Series ; Telemedicine ; COVID-19

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