IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database.

Area of Science:

• Biomedical Engineering
• Health Informatics
• Internet of Things (IoT)

Background:

• Healthcare technology requires significant development, particularly in managing large patient data volumes.
• Existing protocols like MQTT and MLLP struggle with transferring large medical image files to IoT servers.
• Monitoring ultrasound, MRI, or CT image data via IoT presents considerable challenges.

Purpose of the Study:

• To propose a novel IoT model for displaying medical images and patient data on a dashboard.
• To overcome limitations in transferring large medical image data over IoT networks.
• To enhance telemedicine capabilities through improved data monitoring.

Main Methods:

• A Raspberry Pi processes HL7 messages from medical devices (e.g., ultrasound machines).
• Image data is extracted and transferred to an FTP server.
• Raspberry Pi 3 forwards patient information and encrypted image links to an IoT server.
• An NS3-based simulation environment was used for real-time monitoring and performance analysis.

Main Results:

• The proposed system successfully displays medical images and patient data on an IoT dashboard.
• Real-time monitoring of ultrasound image data on the IoT server was achieved.
• System performance analysis demonstrated impressive results.

Conclusions:

• The developed IoT model effectively addresses challenges in transferring and monitoring large medical image data.
• This approach significantly enriches telemedicine facilities by enabling comprehensive data oversight.
• The system offers a robust solution for improving healthcare data management and accessibility.