## 1 Introduction  
The accurate detection and mapping of subsurface utilities are essential for ensuring safety and operational efficiency in excavation and construction projects. This is especially important in urban areas where underground infrastructure is highly dense and often undocumented. Failure to identify subsurface utilities can result in serious accidents, economic losses, and project delays. A notable example is the 2003 Daegu subway fire disaster in South Korea, which led to over 100 fatalities and widespread damage, emphasizing the importance of reliable underground utility detection [1, 2, 3, 4].  
To address such risks, non-destructive geophysical methods have been widely adopted, with Ground-Penetrating Radar (GPR) being one of the most commonly used techniques. GPR operates by emitting high-frequency electromagnetic waves and analyzing their reflections from subsurface features with differing dielectric properties [5, 6]. While GPR is capable of detecting both metallic and non-metallic utilities under favorable conditions,its performance is highly affected by soil conductivity, water content, and material type. Ground-Penetrating Radar (GPR) has been widely used for subsurface detection; however, its effectiveness diminishes in complex soil conditions, such as heterogeneous compositions or high moisture content. Ref. [7] reviewed the application of GPR in agricultural settings and noted challenges in accurately sensing subsurface features under such conditions. Furthermore, ref. [8] highlighted the limitations of electromagnetic methods like GPR, particularly in detecting non-metallic pipelines such as PVC or PE, and emphasized the potential of acoustic-based techniques as alternative solutions. Ref. [9] proposed an improved GPR data processing approach tailored to subsurface utility detection in urban environments, demonstrating a higher detection accuracy even under complex underground conditions.  
To overcome these constraints, the All Materials Locator (AML) has emerged as a promising alternative. Unlike GPR, AML integrates ultra-high-frequency electromagnetic sensing and acoustic/ultrasonic detection to identify subsurface anomalies based on variations in material density and structure. This hybrid approach makes AML less dependent on the electromagnetic properties of surrounding soils, allowing for more consistent detection of both metallic and non-metallic utilities. Preliminary studies suggest that AML offers greater depth penetration and an improved accuracy across diverse soil conditions [10; 11].  
Recent developments in subsurface utility detection have also emphasized the effectiveness of hybrid systems that combine electromagnetic and acoustic sensing approaches, demonstrating an improved performance under variable soil and infrastructure conditions [12].  
However, AML systems may still be influenced by environmental variability, operator technique, and site-specific conditions such as soil heterogeneity--factors that necessitate systematic field validation.  
This study aims to systematically evaluate the performance of the AML system using a nationally certified underground utility test site operated by Sungkyunkwan University. By employing standardized testbeds with both metallic and non-metallic pipelines buried at depths up to 3 m, the study goes beyond manufacturer-driven validations to provide field-based evidence of AML's detection accuracy under regulatory conditions. The findings highlight the system's potential as a reliable alternative to conventional GPR, particularly in detecting deeply buried non-metallic utilities--an area where traditional technologies often fall short.