PURPOSES : This study primarily aims to develop and evaluate a Smart Station - a novel underground pipeline measure system - to overcome the challenges of conventional surveying methods. METHODS : This study built two prototypes of the Smart Station. By reflecting issues revealed through the field tests of the first prototype, this study produced the second Smart Station prototype. The organization of the hardware units in the second prototype was reconfigured to maximize its usability for operators in the field. Furthermore, by developing the ‘Digital Twin X’, an integrated Smart Station management software suite, the second prototype was capable of 1) producing a digital workbook for field operators, 2) managing underground pipeline information, and 3) displaying 3-dimensional maps in and around an underground pipeline. The applicability of the second prototype was examined through three field tests conducted in one open space location, where no urban valley effects were expected, and two locations in a downtown area, with urban valley effects. Given the actual field installation of underground pipelines, this study collected data via both conventional surveying methods and the Smart Station to evaluate the performance of the Smart Station. Analyzing the field data, this study examined the data collection time and position accuracy of an underground pipeline measured by the Smart Station. RESULTS : The field test results revealed that both the conventional surveying method and the Smart Station produced similar performances in data collection time and measurement accuracy in the open space test location. However, in the case of downtown locations affected by urban valley effects, the Smart Station achieved 100 % measurement accuracy while the conventional surveying method achieved 93 % accuracy. It was also observed during the field test that no data were collected due to the constraints of the work schedule and various field conditions (e.g., weather and/or traffic congestion). The data collection times at the open space locations were 10 s for both the conventional surveying method and the Smart Station. However, the data collection times at the downtown locations appeared to be 10 s and 360 s by the Smart Station and the conventional surveying methods, respectively, thereby proving that the Smart Station outperforms the conventional method in its measurement efficiency. CONCLUSIONS : It is envisioned that the Smart Station produces higher work efficiency for field operators as it enables them to collect high accuracy data in a timely and quick manner and not only build a database for the collected data but also vividly visualize it in the field. In the future, it is necessary to conduct additional field tests under various conditions for the in-depth investigation of a Smart Station. In addition, it is expected that the Smart Station will be enhanced by coupling augmented reality (AR) technologies.