## 5 Experiment Result
### Second Scenario: Patient Position Tracking Based on Different Camera Locations  
The second scenario of the OCC-IoMT system, which is designed for patient health monitoring, focuses on a setup involving a TX with a matrix LED and two RX-using cameras. The critical aspect of this setup is the operation of both cameras based on their FOV, which provides a deeper understanding of how the system effectively monitors patients who move between positions. Figure 11 provides a detailed setup of the OCC-IoMT system featuring one TX and two RX. Here, the transmitter is represented by a patient moving from one point to another. The patient is equipped with a device containing a matrix LED that transmits vital health data such as heart rate, oxygen saturation, and body temperature in real time, as well as the value of the panic button. For monitoring purposes, two cameras function like a CCTV, each with an FOV. This setup allows the cameras to alternately monitor the patient as they move from one FOV to another, ensuring continuous, gap-free monitoring, even as the patient moves. The first camera monitors the patient until they move out of its FOV, at which point the second camera takes over. This capability ensures that no information is missed as the patient moves within the monitoring area, and it allows for tracking the patient's location based on the identification of the camera that detects them, demonstrating the system's flexibility in accommodating patient movement and providing accurate, continuous data for medical teams. Similar to the first scenario, the YOLO algorithm is utilized for patient detection and tracking. This algorithm enables the cameras to efficiently recognize and track the movement of patients from one FOV to the next. Once the data are collected, they are stored in a database using REST API, ensuring data integrity and accessibility. Figure 12 displays the results of implementing the OCC-IoMT system. Figure 12a illustrates the detection performed by the YOLO algorithm in the first receiver's FOV. Figure 12b shows the patient moving out of the first receiver's FOV and then being detected by the second receiver, demonstrating how the system identifies and tracks the patient's movement and the transition of FOV from the first receiver to the second. Figure 12c presents a view of the database, displaying the data received from both receivers. Lastly, Figure 12d showcases a web interface accessible to patients, providing real-time information about patients. The OCC-IoMT system effectively demonstrates real-time health monitoring in two distinct scenarios. Scenario one involves two patients (transmitters), each with a matrix LED transmitting vital health data, and a single camera (receiver) processing this data using the YOLO algorithm and relaying it to an edge server for medical team access. This setup ensures continuous monitoring and data accuracy. Scenario two focuses on a single patient moving between two cameras (receivers), each covering a different FOV. This arrangement allows for seamless monitoring as the patient moves, with each camera capturing data as the patient enters its FOV. Both scenarios highlight the system's flexibility and efficiency in tracking patient health data, ensuring no information loss, and maintaining data integrity  
Figure 11: Setup of the OCC-IoMT system featuring one transmitter (TX) and two receivers (RX). through real-time processing and storage. This advanced system exemplifies the potential of IoMT in enhancing patient care and monitoring. Table 2 presents a comparison of functionalities across three different systems. It can be observed that the generated OCC method is capable of competing with existing technologies such as Bluetooth and Wi-Fi. Additionally, the proposed method, based on the IoT platform, can display patient data in real-time with a greater number of sensor detections. Furthermore, the OCC system excels in the areas of security and privacy as it transmits light as the signaling medium, making it immune to hacking during data transmission.