A team from Hunan University in central China has collaboratively developed an intelligent operating system for tunnel boring machines, giving these massive underground giants a "smart brain."

The system, created alongside researchers from China Railway Construction Heavy Industry Co., Ltd, represents a major step forward in autonomous tunnel construction and risk prevention, according to the research team on Saturday.

Often described as "steel dragons," tunnel boring machines (TBMs) are colossal pieces of equipment essential for digging underground passages. Unlike machinery operating above ground, TBMs work in close contact with surrounding rock and soil, making them highly sensitive to geological conditions.

In complex environments, human operators often struggle to adjust the machine's settings appropriately, which can lead to dangerous situations such as ground collapse, excessive settlement, or even loss of control.

To tackle this challenge, Professor Chen Renpeng from Hunan University led a joint research initiative aimed at teaching these machines to "read" the ground, "predict" risks and make precise adjustments on their own.

The resulting intelligent system acts as a real-time guardian for tunnel construction. It continuously collects data from sensors on the TBM, analyzes geological conditions, forecasts potential hazards and automatically recommends optimal digging parameters.

"With this 'smart brain,' we can accurately predict ground settlement and the machine's posture, helping to avoid risks like surface collapse before they occur. It also warns if the machine is in danger of getting stuck and makes intelligent decisions to keep tunneling smooth and efficient," said Professor Zhang Chao, a member of the research team.

Having been deployed on a super-large-diameter TBM in a Shanghai metro project, the system has shown impressive results. It assisted with over 90 percent accuracy in operational decisions and kept deviations in the tunneling direction within 30 millimeters, far surpassing the precision achievable through manual control, the research team noted.

In another project in Guangzhou in south China, the system improved fault diagnosis and maintenance efficiency by 20 percent, boosted equipment utilization by 12 percent, and increased monthly progress by 5 percent, the team added.

The China Highway and Transportation Society has identified the innovation as a crucial key technology for industry promotion.

Chen said that the team will continue to refine the technology and expand its application to more challenging projects, including cross-river and subsea tunnels, supporting safer and smarter development of China's underground infrastructure.