## 1 Introduction
As aforementioned, knowledge or data is gained through sensing devices. Therefore, the sensing layer can be regarded as the first layer in the IoT architecture. This layer consists of sensor networks and embedded technologies, also considered the slowest layer compared to other layers [12]. Above the sensing layer is the communication layer, and its task is to bridge and manage the communication between the sensing and upper layers. These layers include routers, switches, and other similar devices and use several protocols such as CoAP [13] and Message Queueing Telemetry Transportation (MQTT) [14]. The cloud layer is the one-level layer above the communication layer and as the name implies, the cloud layer utilizes cloud and edge computing technologies. In the cloud layer, data are processed and analyzed to obtain more insights, and information and decision-making can be performed [15]. Cloud technologies are currently equipped with artificial intelligence technologies to enable autonomous decision-making [16]. The management layer is responsible for monitoring other layers so that actions can be taken if faults or errors occur on those other layers. Finally, the application layer can interact with end-users directly. It provides applications and services for end-users so that all processes in the IoT can be operated within human control [11]. As illustrated in Figure 1, this architecture forms the foundation for diverse IoT implementations, providing a flexible yet structured framework for various IoT applications. As aforementioned, one of the IoT applications is in the medical field. Notably, there are many specialized fields in IoMT. However, one of the trending research projects regarding IoMT is the development of a Wireless Body Area Network (WBAN) [17]. WBAN aims to provide continuous and automated monitoring of patients as well as insights and knowledge that can be concluded by the medical staff; thereby, responses and actions can be performed more rapidly. Furthermore, WBAN is designed to obtain various data, such as temperature, oxygen saturation, and tension [12], directly from the patient's body, making the health diagnosis more accurate [18]. In indoor scenarios such as medical centers or even hospitals, WBAN can be integrated with local or edge server systems to create an IoMT system that is robust and sustainable in providing data. Currently, RF-based signal communication technologies such as Bluetooth, Ultra-Wideband (UWB), and ZigBee are still widely used to send data from sensing devices in the body area to the upper layer of the IoMT system [19]. Figure 2 shows the illustration of WBAN, which presents a visual representation of how WBAN functions within the IoMT framework. Despite the rising usage of RF-based IoT in medical applications, it has several disadvantages. Since the sensing devices are attached to the body, the communication device should also be located near the body. RF-based communication devices are commonly known to be harmful to the body in long-term usage [20]. This would be unhealthy for anyone, especially a patient with severe illnesses. Moreover, RF-based communication is prone to jamming and intrusion [21], resulting in unsafe users, which in advanced cases can lead to malicious threats or other cyber-attacks [22]. However, despite its potential as a new communication medium, OCC has several drawbacks compared to other communication technologies. OCC is dependent on camera specifications, with commercial cameras mostly having low frame-per-second (fps) rates. This problem can be overcome by using a more sophisticated camera. Additionally, in a non-line-of-sight (NLOS) situation, the communication performance deteriorates, unlike other communication modes. OCC requires high visibility on the transmitter. This issue can be addressed by using several cameras in an environment, improving the OCC system's performance. While the transmitter may not be visible to one receiver, it might be visible to other cameras.