## 1 Introduction
OCC is exceptionally secure, as it is almost negligibly affected by the reflected component of the light signal [26]. Unlike RF-based technologies, OCC is less affected by interference. The interfering element can be extracted spatially from the image sensor, because each pixel acts as a photo detector. The BER using OCC is almost zero when the communication distance is short [28; 29; 30; 31]. The achievable data rate of OCC is approximately 55 Mbps, which is also comparable to other low-power-based technologies [25]. Although OCC mainly utilizes the visible light spectrum, it can also operate in the infrared spectrum. Infrared wavelengths are invisible to the human eye and remove the LED flickering that can be bothersome to the patients. In addition, LEDs can be modulated with very low power. By virtue of these characteristics, OCC is a very promising solution in healthcare signal transmission. LED can be embedded in wearable devices, and a camera is utilized to receive the bio-signals. However, data transmission in OCC is instantly terminated if the signal transmission path is blocked by any obstacle. In addition, LED must appear inside the angle-of-view (AOV) of a camera. Furthermore, a direct line-of-sight (LOS) connection is required for successful communication. Considering both the utilities and limitations of OCC, we propose a novel hybrid architecture that combines OCC and BLE for real-time healthcare signal transmission to a remote monitor. We consider the transmission of ECG data that particularly focus on heart rate variability. The main contributions of this work are listed below. * A patch that is connected with an ECG sensor network is proposed. It is constructed using an LED array and a BLE transmitter. The signal is modulated in the LED or BLE and sent to the respective receiver. Static surveillance cameras are utilized to receive the LED data. * We propose an algorithm that selects the appropriate network in a specific scenario. OCC has been provided with initial priority in the selection mechanism. We employ both single and multiple cameras to compute the selection probability. The AOV can be remarkably increased by using multiple cameras. * We apply fuzzy logic (FL) to select the most excellent camera. FL is an approach that uses variable truth values ranging from 0 to 1 to generate a certain decision. Different parameters of the OCC performance are investigated while applying FL. The center-of-gravity (COG) method is used to perform defuzzification. * The selection mechanism is initiated by using a network access request (NAR) generated from the patch circuit. The NAR is produced on the basis of a patient's current condition. Therefore, power consumption can be minimized when the condition is well controlled. * To confirm connection reliability, we propose a handover mechanism from OCC to BLE or vice versa. The data are transmitted to a gateway for further transmission to a remote monitor. The symbols used in our paper are listed in Table 1. The remainder of this paper is organized as follows. Section 2 provides an overview of the current IoT technologies utilized in healthcare. Section 3 introduces the patch circuit and the proposed hybrid infrastructure and presents the channel characteristics of OCC and BLE. Section 4 represents the algorithms for generating a new NAR, network selection for this NAR, and handover from OCC to BLE or vice versa. Section 5 evaluates the performance of the developed selection mechanism in a simulation study. The paper concludes with Section 6.