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

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.

Automated summary

In recent years, the healthcare system and its surrounding technology have become an important area for development. Significant research has been conducted on biomedical and telemedicine studies, leading to improvements in various areas. However, transferring large amounts of data, such as images, to IoT servers using certain protocols can be difficult and time-consuming. To address this issue, a proposed model involves displaying images and patient data on an IoT dashboard, with a Raspberry Pi processing and transferring the image data to an FTP server. With an implemented simulation environment, the real-time ultrasound image data monitoring on the IoT server has shown impressive system performance, which will enhance telemedicine facilities for both patients and physicians.