梳理近年来国内外施工隧道自动监测相关文献，探讨测量机器人、数字图像处理监测技术、雷达监测技术、光纤传感监测技术等在实际工程中的应用研究现状及优势。结果表明，测量机器人、数字图像处理监测技术、雷达监测技术、光纤传感监测技术能够有效捕获隧道位移变形和结构受力的动态变化，在提高监测数据的精确度、保证实时性方面具有显著优势，但存在设备成本高、技术单一、自动化程度低、监测空间受限以及监测数据处理和分析复杂等问题，限制了自动监测技术在施工隧道中的广泛应用，距真正实现施工全程自动化、智能化监测仍有较大差距。而物联网技术在监测数据的智能传输与集中处理方面展现出巨大潜力，机器学习算法和数字孪生技术在处理大量复杂监测数据和提高预警准确性方面也具有显著优势，但仍需克服预测模型的依赖性、计算成本等问题。展望未来，隧道施工自动监测技术的发展趋势将集中于数字化、精准化和集成化，向更高层次的智能化方向发展。

The authors systematically review recent global literature on automatic monitoring technologies in tunnel construction, focusing on their applications and current research status. Technology analyses include measurement robotics, digital image processing and monitoring, radar monitoring, and fiber optic sensing and monitoring. The findings reveal that these technologies effectively capture dynamic changes in tunnel displacement, deformation, and structural stress, offering significant improvements in the precision and real-time capabilities of monitoring data. However, several challenges remain, including high equipment costs, dependence on specific technologies, low levels of automation, limited monitoring coverage, and the complexity of data processing and analysis. These limitations hinder the widespread adoption of automatic monitoring technologies in tunnel construction, leaving a considerable gap in achieving full automation and intelligent monitoring. The Internet of Things shows great promise for enabling intelligent transmission and centralized processing of monitoring data. Similarly, machine learning algorithms and digital twin technologies offer significant advantages in handling large volumes of complex monitoring data and enhancing the accuracy of early warnings. Nonetheless, challenges such as reliance on predictive models and high computational costs need to be addressed. Looking ahead, the development of automatic monitoring technologies in tunnel construction is expected to focus on digitalization, precision, and integration, paving the way for advancements toward higher levels of intelligence.