## 3 Methods
### Development of Digital Device Using Arduino and Sensors  
This study used sensors to acquire data on dust density, gas concentration, and road surface conditions. A dust sensor (PMSA003) was used to measure the density of dust generated at the mining site (Figure 3A). PMSA003 is a type of digital and universal particle concentration sensor that can be used for obtaining the concentration of suspended particles in air. The sensor operates at \(-40\) to \(80\)\({}^{\circ}\)C and can detect relatively small particles of \(<\)2.5 \(\upmu\)m and particulate matter 2.5. The sensor detects dust based on the laser scattering principle using a laser to radiate suspended particles in the air and then collects scattered light. Furthermore, it predicts the dust density by obtaining the curve of the change in scattering light with time. It has an effective dust density range of up to 500 \(\upmu\)g/m\({}^{3}\) and a resolution of 1 \(\upmu\)g/m\({}^{3}\). Figure 1: (**a**) Panoramic image, (**b**) DSM, (**c**) orthoimage, and (**d**) three-dimensional image of Taeyoung EMC’s Samdo mine. An MQ-135 gas sensor was used to measure the concentration of harmful gases that may have been emitted during the mining process (Figure 3B). The MQ-135 gas sensor detects gases such as ammonia, benzene, alcohol, and carbon dioxide at values ranging between approximately 10 and 1000 ppm and requires a preheating time of approximately 3 min to measure the correct value. Because the sensor's sensitivity depends on the type of air, the gas sensor is not sensitive to the presence of the gas sensor. Figure 3: (**A**) Dust sensor, (**B**) gas sensor, (**C**) LiDAR, (**D**) Arduino Uno, (**E**) Bluetooth module, and (**F**) a digital device that combines Arduino and sensors. Figure 2: Concept of information sharing among vehicles through a smartphone application. of gas to be measured and the environment, calibration in a controlled environment is necessary for accurate measurements. However, because the Samdo mine, our case study, is a limestone mine, the emission of harmful gas is insignificant; thus, the precise correction process for individual sensors was omitted because the primary purpose was not to measure the exact gas concentration. All experiments were performed after preheating the sensor for at least 3 min to properly observe the change in the gas concentration. A point-based light detection and ranging (LiDAR) sensor that can detect distances using light was used to understand the road surface conditions at the mining site. Garmin's LiDAR-Lite v3 HP (Figure 3C) was used, and the product could measure a distance from 5 cm to 40 m, with an accuracy of approximately 2.5 cm and a resolution of 1 cm. This study used LiDAR to identify the remote road surface conditions and risks in advance. Although LiDAR allows one to indirectly identify the road surface conditions by measuring the distance from the road surface, vibration measurement can be a more direct indicator to quantify the direct impact on the vehicle. Various sensors can be used for vibration measurement; however, because this study used a smartphone, the vibration was measured using an inbuilt accelerometer in the smartphone. The accelerometer can measure acceleration in the X, Y, and Z directions around a specific axis of the sensor. Because the gravitational force always works even in the absence of vibration, a low-pass filter was applied to the acquired acceleration data to remove gravitational acceleration and quantify the vibration value. Additionally, a spatial analysis of the data obtained from each sensor was performed, combined with location data. This study used a GPS sensor built into a smartphone to obtain vehicle location information. Therefore, vibration and location measurements were performed using a smartphone, and other data were obtained using other sensors. These sensors were connected to an Arduino Uno microcontroller (Figure 3D), such that field information could be acquired in real time.