## 3 Experiments of the RB Control in the Proposed Greenhouse System  
As far as we know, the proposed greenhouse system based on autonomous RB controls is novel, since we control RBs for providing optimal sunlight for plants inside the greenhouse. We address experiments of the RB control in the proposed greenhouse system. Using a small box, we made a small greenhouse to test our RB control algorithms, as plotted in Figure 3. We install this greenhouse on outdoor open environments, so that sufficient sunlight can be provided onto the greenhouse. The experiments are performed for three hours (11:00-14:00). Figure 3 plots the RB installed in front of the greenhouse. Figure 3 shows a breadboard inside the box. On the breadboard, we install two light sensors.  
We explain the experiment setup of our research. Arduino is an open-source micro-controller, which is widely utilized for implementing IoT devices [16]. We utilized an Arduino Nano which is a miniaturized model with an ATmega328 processor (Microchip Technology Incorporated, Chandler, AZ, USA).  
Arduino Nano (Arduino, Somerville, MA, USA) is utilized to control the RB, and the RB is controlled using two encoder motors at both sides of the RB. We utilize encoder motors to control the RB, while measuring the RB angle in real time. Inside the small greenhouse, we attached infoils to enable sunlight reflection. In addition, two light sensors are installed on the breadboard inside the greenhouse. The measurements of the light sensors, RB angles, and the associated time information are stored in the SD card. By controlling the encoder motor attached to the RB, we control the light intensity inside the farm. We can control the RB angle precisely, since we install encoder motors. In Figure 3, two encoder motors are marked with two arrows, respectively.  
Our control settings are as follows. In Algorithm 1, we utilize \(\epsilon=1\) min, since the light sensors can obtain stable light measurements within \(1\) min. In experiments, we utilize the angle step size as \(\Delta=5\) degrees. In addition, \(t_{h}\) is set as \(25\) Lux.  
Experiments are carried out to demonstrate the performance of the proposed RB controls in Section 2.1. The experiments are performed for three hours. Inside the greenhouse, we measure the light intensity at every one minute, i.e., \(\epsilon=1\) min.  
Recall that \(optLux\) denotes the light intensity set by the operator. We set \(optLux=175\) lux in our RB experiments.  
Figure 3: Using a small box, we made a small greenhouse to test our algorithms. This figure shows the RB installed in front of the greenhouse. Arduino Nano is utilized to control the RB, and the RB is controlled using two encoder motors at both sides of the RB. We utilize encoders to measure the RB angle in real time. Inside the greenhouse, we attached infoils to enable sunlight reflection. Two encoder motors are marked with two arrows, respectively. This figure shows a breadboard inside the box. On the breadboard, we install two light sensors.  
Figure 4 plots the experimental results proving the effectiveness of proposed RB controls in Section 2.1. Algorithm 1 is utilized to control the RB, for providing the optimal amount of sunlight which is set by the operator. The mean light intensity \(m_{lux}\) remains close to \(optLux\) (175 lux) under the light control system (Algorithm 1). This proves the effectiveness of Algorithm 1 in providing the optimal sunlight for plants.  
Figure 5 shows the change of RB angle (in degrees) associated with the experiments in Figure 4. In Figure 5, Algorithm 1 is utilized to control the RB for providing the optimum amount of sunlight. Once we set a RB angle using Algorithm 1, we maintain the angle for \(S=10\) min until moving the RB again.