## 1 Introduction  
Most haulage roads in mines are unpaved, which can increase the haulage time and cause significant fuel consumption and vehicle damage. If the surface of a haulage road is very rough, it may cause accidents or personal injuries. Recently, the number of accidents caused by mining activities has decreased [1]. However, in Korea, the number of victims of haulage accidents in the last decade was approximately 60, indicating that haulage accidents still occur frequently [2]. However, in the United States, accidents during haulage account for 20% of accidents caused by mining activities [3]. Therefore, to establish a safer mining environment, the risk of haulage operations should be reduced by detecting and preventing risks at the mining site in advance. Therefore, the driver's line of sight should be analyzed; potential hazards should be detected at the mining site; and necessary actions should be taken in advance. [PERSON] et al. [4] predicted dangerous areas within an open-pit mine haulage road using a geographic information system (GIS)-based viewshed analysis. A study was conducted to reduce haulage time and potential risk by combining a GIS-based multi-criteria evaluation and an optimal route analysis [5]. Recently, various attempts have been made to improve safety at mining sites using Internet of Things (IoT)-based network technologies. [PERSON] et al. [6] developed a smartphone application that can grasp the current location of haulage trucks underground by communicating with Bluetooth beacons attached to underground mines. Furthermore, a study was conducted to prevent accidents by applying Bluetooth low-energy technology to individual haulage trucks or worker helmets to warn when a truck approached a worker [7]. Many studies to determine the operation and safety status of vehicles and heavy equipment in open-pitmines by installing GPS have been conducted [8, 9], and commercialized systems have been developed. Additionally, various sensors and wireless communication technologies (such as Bluetooth [10, 11], ZigBee [12, 13], and Wi-Fi [14, 15]) have been combined to monitor vibrations, dust, and harmful gases in underground mines [16, 17, 18, 19]. However, these studies are primarily limited, in that changes can only be observed at a specific point by fixing a sensor at a specific location, and wearable systems can only detect nearby environment. For workers to detect and quickly respond to risks at the mining site, they should first understand the environment; second, they should understand the environment of other workers or other areas. However, few studies on the detection of the surrounding environment of a moving worker, vehicle, or equipment, and systems to share acquired information have been conducted. Although there are a few cases of IoT technology or smartphone applications in the mining industry, more studies on road conditions and air quality have been recently conducted in other fields. Table 1 summarizes these studies. In some cases, the surface conditions of a road were evaluated by measuring vehicle motion using motion sensors embedded in black boxes or smartphones [20, 21, 22, 23, 24, 25]. Some studies considered the vehicle's location using a GPS sensor, whereas others gradually analyzed vibrations. In most studies, a vehicle's vibration could be transmitted to a server through a smartphone or IoT module; however, the status of other vehicles could not be checked in real time. Additionally, although they used sensors embedded in the smartphone, additional sensors were not combined. Numerous researchers have used IoT devices in individual vehicles to indirectly detect road conditions, whereas national institutions or large corporations have applied IoT sensors directly on the road. A connected sensor network was developed in Scotland to provide real-time road conditions, such as temperature, moisture, and potential culvert blockages, across 10,000 km of rural roads [26].