# IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database
### Related Works  
Therefore, a model has been proposed that might be utilized to implement a low-cost strategy for the protection of human life on the battlefield [15]. Another study shows how IoT significantly affects the healthcare system [16]. A solution in another study describes a patient wearing a single wristband to capture vital sign data, decreasing the number of sensors required per individual to just one [17]. The study provides a schematic representation for a low-cost IoT-based biomedical kit that can monitor vital signs for persons in rural areas at a rapid rate with an accuracy of 98% and 95% for temperature readings and pulse rate, respectively. In a further study, Musical Chairs is applied to two well-known image recognition models, AlexNet and VGG16, and is implemented on a Raspberry Pi network. In terms of time and energy performance, their systems were compared to the Tegra TX2, an embedded low-power device featuring a six-core CPU and a GPU. This configuration demonstrates how Musical Chairs enables the collaboration of IoT devices to achieve equal real-time performance without spending the additional costs of running a server [18]. Overall, our approach proposes helping patients deal with challenging situations while doctors are absent. It does not help in emergency cases where patients must be admitted to hospitals, but it does help in giving appropriate first aid protocols for dealing with emergencies. Most people who are suffering from common symptoms of an illness can benefit from this idea.  
Medical images are typically disseminated to numerous organizations or within organizations for correct diagnosis. Therefore, the exchange of medical data is required to improve the quality of healthcare services. Users will be able to employ accessible and distributed cloud computing platforms, and so IoT device connections through the internet and advancements in cloud computing technology are required. The ability to watch real-time picture data from an IoT server simplifies the process for both patients and clinicians. However, due to low data transmission rates and payload size, dependable and real-time picture transmission in IoT monitoring systems is regarded as very difficult. IoT protocols are message-centric wire protocols developed for M2M communications that allow the transfer of telemetry-style data in the form of messages from devices to a server or small message brokerage over high latency or limited networks. MQTT, MLLP and CoAP meet these requirements by utilizing tiny message sizes, message management, and lightweight message overhead. Real-time picture data monitoring systems using MQTT and MLLP protocols are difficult for IoT servers to handle. This study proposes a strategy to remedy this problem.  
The main contributions of this study are given below:  
1. Machine-to-machine-based communication with an IoT server using HL7 message processing.
2. Medical diagnoses image data stored in an FTP server with unique encrypted image links.
3. A real-time image data display with patient info in an IoT server.  
The rest of the paper is organized as follows: (i) proposed methodology, with discussion on how to transfer telemetry data with images; (ii) results analysis; (iii) discussion, and (iv) conclusions.