# IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database
## 2 Materials and Methods
### Ultrasound Machine to Raspberry Pi HL7 Messaging Process
#### 2.1.1 HL7 Block Formation and Messages
A server-side module is used as the secure ultrasound real-time data channel and controls how ultrasound frame data are sent from the server to the client [20]. This data line connects directly to the ultrasonic machine, while parameters are managed via the secure real-time control route. Furthermore, the authors of one article used the LoRaWAN protocol for data transfer, whereas we merely produced byte data via URL encryption on the IoT server, which resulted in a long data response time on the IoT server [21]. Another article on sensor utilization used a smart healthcare system to collect data from the hospital environment by monitoring fundamental patient health indicators such as heart rate and temperature, whereas we use small packet data for displaying and generating large data with such health indicators and image sources [22]. Another study we encountered gave a process for creating professional, easy-to-understand visualizations of the data for seamless integration into clinical practice, whereas we have successfully developed a

Figure 13: Line chart diagram based on the response time (**a–c**). request-response-based data transfer and thus were able to reduce the data collision rate to a tolerable level [23]. In another piece of research, they attempted to adapt a system in an automated manner to follow the condition of patients when physicians are absent by employing SHS technology, which ensures that therapy is administered to a person in the absence of a doctor [24; 25], which is quite dangerous. However, according to our system, patients do not need to rely on such risky treatment; they can easily send their issues in a request, and the system will store those data in a dashboard where doctors can monitor their registered patients' issues and provide feedback on them from anywhere and at any time. The main hardware components are all based on the Raspberry Pi 3 Model B [26], and it enhances overall healthcare delivery by allowing patients and clinicians to interact in a variety of ways. Additionally, we have used only RSPI3 and large packet data as encrypted image links over FTP for displaying data in the IoT server, which consumes less time. In contrast to the other studies above, our system overcame the large data transfer issue and displayed the image data, which may be a large amount of data. The response was returned on time and securely. Now we will discuss the conclusions of our proposed method and focus on whether it is the best method and if it is suitable for an IoT server. ## 4 Conclusions

Technology is constantly improving around the world, which is how IoT is becoming a more practical form of technology. Every industry is becoming more advanced because of IoT. The healthcare industry has also embraced IoT, and this paper is a straightforward reflection of how IoT may benefit the industry. Because many people may not have the opportunity to visit world-class healthcare experts, we created an IoT-based Ultrasound Image Monitoring System that allows healthcare experts or doctors to easily monitor and diagnose any patient from anywhere in the world, thanks to the benefits of cloud-based IoT systems. Our proposed method is applied over IoT from a hospital database, so it has some limitations e.g., for large data transfers it takes more time in real-time than the simulation, and the response time depends on the internet bandwidth. In this approach, both doctors and patients will be able to save time and avoid superfluous costs such as making appointments with doctors, transportation fees, and other costs just by using our system properly. We hope that the technology we developed, as well as related research, will eventually bring about progress in the healthcare industry. Further modifications and improvements to the system will improve the overall service of the healthcare business around the world. Conceptualization--M.H.-A.-R. and methodology--O.C. ; formal analysis and resources--M.M.R.