Towards Interactive Medical Content Delivery Between Simulated Body Sensor Networks and Practical Data Center

Area of Science:

• Biomedical Engineering
• Computer Science
• Information Technology

Background:

• The integration of Internet of Things (IoT), big data analysis, and cloud computing is transforming traditional medical information systems.
• Cloud-based smart healthcare applications are gaining significant attention for their potential to improve patient care and operational efficiency.
• Existing systems face challenges in real-time data transmission and cost-effective testing.

Purpose of the Study:

• To apply semi-physical simulation technology to cloud-based smart healthcare systems.
• To enable the transmission of real medical data to practical data centers using a simulated Body Sensor Network (BSN).
• To reduce the costs associated with device procurement and personnel for network setup and testing.

Main Methods:

• Designing an OPNET packet structure tailored for medical data transmission.
• Defining a gateway node model to interface simulated BSN with practical data centers.
• Building a custom protocol stack to manage data flow within the semi-physical simulation environment.
• Conducting extensive simulations of real data transmission across interconnected simulated and practical networks.

Main Results:

• Successful transmission of real medical data within a semi-physical simulation environment.
• Validation of the custom protocol stack and gateway node model for effective data routing.
• Demonstration of reduced costs for device and personnel compared to fully practical network setups.
• Generation of simulation data providing a reference for parameter settings in fully practical networks.

Conclusions:

• Semi-physical simulation is a viable and cost-effective approach for developing and testing cloud-based smart healthcare systems.
• The proposed OPNET packet structure, gateway node model, and custom protocol stack facilitate reliable data transmission from simulated BSNs.
• This methodology offers a practical reference for optimizing fully practical healthcare networks, minimizing resource expenditure.