## 5 Conclusions  
This study developed a technology that can monitor the environment of mining sites and share information among vehicles by attaching digital devices combined with various sensors. The dust density, gas concentration, and road surface conditions were observed at a mining site using a dust sensor, a gas sensor, and LiDAR, respectively. The vehicle's location and vibration values were measured using GPS and accelerometers built into the smartphone. The data measured using the digital device were transmitted to the smartphone application through a Bluetooth module, and the sensor value could be checked in real time through the application. The Firebase database was used to share the data acquired from each vehicle, allowing each application to continuously upload its own data and receive data from other applications. Before applying the developed system to the mining site, a preliminary test was performed using RoboMaster S1, a wireless control  
Figure 11: Analysis results of the spatial distributions of vibration, distance from the surface, dust concentration, and gas concentration. Sections A and B have rough road conditions.  
vehicle, at Samcheok Campus, Kangwon National University. The measured data differed according to the road conditions. At the mining site, four vehicles were tested along a haulage road. The vibrations of the vehicles were high at the mine adit where the working vehicles were concentrated. Therefore, we concluded that the road surface required to be improved, or more attention should be paid to these areas. Because dust inevitably occurs during work, the dust density was relatively high at the mine adit; however, most workers wore dust masks and were in vehicles. Thus, direct harm was insignificant. However, long-term inhalation of dust can be harmful to the human body; therefore, workers working outside the vehicle should wear a dust mask with particular caution. In this study, the system was applied to ordinary vehicles to avoid interference with work at the mining site. However, in the future, we plan to improve the system and apply it to several field hualage trucks. Consequently, the battery system should be improved to connect the power of the vehicle to the developed digital device. In addition, the data processing method and server system should be improved such that data can be processed and shared quickly, even when many vehicles access the system. If multiple haulage trucks share information and accumulate data, a more reliable risk area analysis could be possible across the entire mine area through a big-data analysis in the future. Furthermore, if this study is combined with IoT-based underground mine communication technology, the locations of vehicles could be identified, and environmental data could be acquired within an underground mine.  
Conceptualization, S.-M.K.; Formal analysis, H.K.; Methodology, S.-M.K.; Software, H.K. and S.-M.K.; Writing--original draft, H.K., W.-H.L. and C.-H.L.; Writing--review and editing, S.-M.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by (1) an Energy and Mineral Resources Development Association of Korea (EMRD) grant funded by the Korea government (MOTIE) (Data science based oil/gas exploration consortium) and (2) a 2019 research grant from Kangwon National University.  
The authors declare no conflict of interest.