A Virtual Reality Platform for Safety Training in Coal Mines with AI and Cloud Computing - Mei Li; Zhenming Sun; Zhan Jiang; Zheng Tan; Jinchuan Chen (Discrete Dynamics in Nature and Society)
Coal mining, regarded as a high-risk industry, has a strong demand for virtual reality (VR) to fulfill safety and emergency rescue training. In the past ten years, VR technology has significantly improved miner training on both the hardware and software side. However, it still has some drawbacks, such as expensive and unsuitable hardware, lack of satisfactory user experience, without direct browser access, and lack of humanized and intelligent design. To solve these problems, a cloud-based VR system is designed for the training of coal miners in this paper. The system, with browser/client architecture, includes eight modules demonstrating the full procedure of an underground coal mine. The online cloud-rendered video streaming is adopted to provide enough computing and rendering power and hence a better browser-based user experience. Furthermore, game artificial intelligence (AI) is also introduced into the system to increase the emotional exchange between the system and users. Unlike traditional VR training software, this system designs two virtual miners to enhance the experience of trainees. The first virtual miner is a task-oriented non-player-character (NPC) which conveys general knowledge about the mine and guides the users in visiting the underground work sites. The second virtual miner is a disaster-oriented character which prepares the users for typical disasters. The system has been successfully implemented in a laboratory environment, and its performance has been validated. Yet, further practices are needed to stimulate more innovative applications of VR-based miner training and disaster drilling.