Water leakage in metro systems poses a persistent threat to structural durability and operational safety, particularly in water-bearing environments where leakage-induced deterioration may propagate through interconnected stations. While previous studies have extensively investigated leakage mechanisms and local structural responses, limited attention has been paid to the system-level vulnerability of metro networks under leakage disturbances, particularly the lack of an integrated framework linking leakage susceptibility and network characteristics. To address this gap, this study aims to develop an integrated framework for assessing station-level vulnerability in metro networks by incorporating both network characteristics and leakage susceptibility factors. Methodologically, network properties are first quantified by integrating topological structure and passenger flow characteristics. Leakage susceptibility is then evaluated using a fuzzy comprehensive evaluation method based on field investigation data. A combined weighting approach is further employed to integrate network and leakage indicators into a unified vulnerability assessment framework. Finally, a Monte Carlo probabilistic failure model is introduced to evaluate system robustness, and station vulnerability is ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The results indicate that leakage-related factors contribute dominantly to station vulnerability, accounting for approximately 62.4% of the overall weight, highlighting their critical role in metro system performance degradation. Several stations are identified as high-risk nodes due to the combined effects of unfavorable hydrogeological conditions and topological importance. The proposed framework can support infrastructure managers in prioritizing inspection scheduling, preventive maintenance, and targeted reinforcement, thereby enhancing the resilience of metro systems against leakage-induced disruptions. Future work should incorporate multi-temporal operational data and real-time monitoring information, and further validate the model using long-term maintenance records to improve its practical applicability.

The adoption of Information and Communication Technology (ICT) in construction projects enhances competence, fosters partnership, and promotes innovation. However, challenges related to ICT implementation persist, particularly in emerging nations. This study investigates the factors of ICT adoption in public building construction projects in Mekelle City, Ethiopia. Using a questionnaire, 75 construction professionals were surveyed, and 8 respondents were purposively selected for in-depth qualitative interviews. Key factors recognized using linear regression include lack of commitment by company management towards ICT (B = 1.152, p = 0.040), security concerns/privacy fears (B = 0.818, p = 0.005), cost of training ICT professionals (B = −0.676, p = 0.044), and limited benefits return on investment in ICT (B = −0.480, p = 0.023), respectively. Quantitative outcomes were verified with qualitative perceptions, providing an inclusive understanding of the factors. Even though the same factors have been recognized in other emerging nations, this study examines how these obstacles work within the public construction sector, branded by regional construction procurement activities and official resource restrictions. By linking known factors with different previously known stages of the construction project lifecycle, this research recommends a framework for the public construction project delivery system in Mekelle city. The research output provides empirical, context-specific evidence on the relative importance and ranking of factors influencing ICT adoption in public building construction projects, where such evidence is currently scarce despite ongoing public infrastructure development. The outcomes deliver actionable recommendations for policymakers, professionals, and researchers. Limitations include dependence on self-reported data, a cross-sectional design, and a limited geographic scope. Future studies should emphasize longitudinal evaluations and comparative studies across Cities to assess the influence of involvement.

Bridge inspection traditionally relies on scaffolds, snooper trucks, and aerial robots for hard-to-reach areas beyond the visual line of sight of inspectors. This study automates the collaborative inspection workflow for multiple users when inspecting hard-to-reach bridge sections by interfacing low-cost multimodal sensors mounted on a magnetically wheeled climbing robot with augmented reality devices in a cyber-physical system. Non-destructive and visual sensors provide near real-time information of automated steel thickness measurements and visual observations of corrosive regions, respectively. The visual sensors also support robot teleoperation. The cyber-physical system is evaluated for its user-friendliness and performance. The system performance is quantified by the live streaming lapse and the execution time for non-destructive testing in augmented reality. Audio notifications are effective for simple training instructions as they help complete 77.8% execution tasks in 0.33 minutes, while video demonstrations are preferred for complex instructions to complete 88.9% tasks in 0.29 minutes. The video captured from a GoPro mini camera is received by the inspectors with approximately 1 second delay when wirelessly transmitted to the host, while it takes 0.122 seconds over cabled transmission.