Underground mining safety and productivity are increasingly challenged by deeper extraction, complex geological conditions, confined workspaces, and dynamic production activities. Hazards such as rock instability, hazardous gases, water inrush, equipment failures, and limited visibility restrict the effectiveness of conventional inspection and expose personnel to high-risk underground environments. Intelligent inspection technologies, integrating advanced sensing, mobile robotic platforms, communication systems, and artificial intelligence, provide emerging solutions for continuous monitoring, condition assessment, and early risk warning. This review synthesizes recent advances in intelligent inspection technologies for underground mines across six major targets: rock mass conditions, ground support systems, ventilation systems, haulage systems, personnel safety, and underground water hazards. Representative technologies, practical applications, and current limitations are summarized. Future research directions are discussed with an emphasis on multi-source information integration, autonomous inspection, intelligent decision support, and reliable field deployment. This review aims to support the development of safer, more efficient, and more resilient underground mining operations.
Public health emergency risk assessments commonly summarize likelihood and impact, but categorical risk matrices may not fully represent the population-exposure burden created by multi-hazard portfolios. This nationwide ecological study analyzed municipality-level summaries from 161 Serbian local administrative units assessed with the World Health Organization Strategic Toolkit for Assessing Risks (WHO STAR) in 2024. In addition to the supplied ordinal STAR measures, we derived an analytical probability-impact product (PIP), cumulative hazard-exposure burden (CHEB = hazard count × reported unit-level exposure proportion), exposure-weighted PIP (PIP × exposure), portfolio risk burden (PRB = PIP × CHEB), and a sample-relative 0–100 Integrated Portfolio Disaster Risk Index (IPDRI). Geographic Information Systems (GIS)-based thematic mapping was used to integrate the analytical dataset with local administrative boundaries and to visualize the spatial distribution of the original STAR indicators and derived burden measures. Primary inference combined rank-based methods with Pearson correlations, Welch tests, robust analysis of variance, non-circular sensitivity models, and exploratory cluster analysis. The supplied STAR risk distribution was predominantly moderate (83.2%), with 11.2% low and 5.6% high. Risk was most strongly associated with probability (Spearman’s ρ = 0.534, 95% bootstrap CI [0.357, 0.683], p < 0.001) and frequency (ρ = 0.360, p < 0.001), and differed substantially across 25 districts, H(24) = 81.95, p < 0.001,ε2 = 0.426. Applying STAR matrix thresholds to aggregate PIP reproduced the supplied risk category in 75.8% of units (quadratic weighted κ = 0.484), indicating only moderate aggregate concordance. IPDRI averaged 43.64 (SD = 21.45) and showed weak, non-significant correspondence with the supplied ordinal STAR risk category (Spearman’s ρ = 0.104, p = 0.187; Kendall’s τ-b = 0.084). Its strong Pearson correlation with CHEB (r = 0.889, p < 0.001) was construction-dependent and did not constitute independent empirical validation of the index. IPDRI differed across macroregions, Welch F(2, 53.15) = 10.11, p < 0.001, and districts, Welch F(24, 38.79) = 14.12, p < 0.001. An exploratory three-cluster solution (silhouette = 0.549) identified different local assessment profiles that also differed in the supplied STAR risk category, F(2, 158) = 12.72, p < 0.001, η2 = 0.139. However, these differences represent descriptive within-dataset associations rather than independent external validation. The findings indicate that STAR risk intensity and exposure-weighted portfolio burden capture complementary dimensions of local public health emergency risk and should be interpreted jointly in preparedness planning.
Building excavations in urban environments involve significant safety challenges arising from complex geotechnical conditions, adjacent structures, and construction uncertainties. This study proposes an integrated framework for identifying and prioritizing excavation safety risks and for quantitatively assessing their schedule consequences under uncertainty. An initial literature review identified 25 excavation-related safety risks, which were subsequently evaluated using the Fuzzy Delphi Method with input from 25 experts. The evaluated process resulted in the validation of 18 safety risks. The Shannon Entropy method was then employed to determine the relative importance of five project-performance criteria, while the VIKOR method was used to rank the identified risks based on expert assessments from 156 construction professionals. The five highest-ranked risks were transferred to a schedule-focused Monte Carlo Simulation (MCS) of a steel truss-supported excavation project in Karaj, Iran. The Delphi survey screening scores are interpreted as expert-derived plausibility scores and are converted to associated subjective scenario probabilities through proportional possibility-to-probability normalization. The simulation results demonstrated that the inclusion of risk-related uncertainties increased the project duration from 62 days to approximately 132.5 days. A robustness check against equal scenario weights produced only small changes in the representative Phase 1 and Phase 2 expected durations (1.42% and 1.81%, respectively), indicating limited local sensitivity to the selected probability transformation. The principal contribution of the study is the explicit, excavation-specific linkage between expert consensus, multi-criteria risk prioritization, and probabilistic schedule-consequence analysis, and an uncertainty-transformation robustness check.
Manual stair transport of bariatric patients imposes substantial physical demands on firefighters. This study evaluated the effects of manikin weight and transport direction on physiological responses during simulated stair transport. Twelve male professional firefighters, organised into three four-person teams, transported a bariatric (215.5 kg) and a standard-weight (85 kg) manikin up and down a staircase. Pulse rate and respiratory rate were measured before and immediately after transport, with pulse rate reassessed after one minute of recovery. Perceived exertion was assessed using the Borg scale. Data were analysed using two-way repeated-measures analysis of variance (ANOVA) and paired comparisons. Manikin type significantly affected changes in pulse rate and respiratory rate and short-term pulse rate recovery. Transport direction significantly affected pulse rate change and recovery, but not respiratory rate change. The mean increase in pulse rate was greater during upward than downward bariatric transport (48.17 ± 16.94 versus 25.83 ± 22.96 beats/min; p = 0.044). Borg scores indicated high perceived exertion in both directions, without a statistically significant difference between them. These findings support combined physiological and perceived-exertion monitoring in firefighter training and the development of safer bariatric transport procedures.
Work zones are essential for infrastructure maintenance, yet remain among the most hazardous environments for both workers and motorists. Despite widespread use of Temporary Traffic Control (TTC), incident rates remain elevated, suggesting limitations in current practices and insufficient integration of Internal Temporary Traffic Control (ITTC). This study employs a mixed-methods survey design to evaluate practitioner perceptions of TTC and ITTC effectiveness, identify perceived incident contributing factors, examine implementation challenges, and assess mitigation measures. Data were collected from 60 experienced transportation professionals using structured Likert-scale questions and open-ended responses. Quantitative data were analyzed using repeated-measures ANOVA to compare perceived incident contributors and mitigation effectiveness, while qualitative responses were analyzed using thematic analysis with affinity-based clustering of practitioner responses. Results indicate that distracted driving (M = 9.2) and speeding (M = 8.3) were perceived as the dominant contributors to work-zone crashes, significantly exceeding improper TTC and ITTC implementation. Among mitigation measures, visible police presence was rated most effective (M = 8.0, p < 0.001), outperforming automated ticketing and static pre-construction planning. Qualitative thematic analysis identified seven improvement domains: work-zone design and management, enforcement and speed control, driver education, worker training and certification, policy development, technology solutions, and inter-agency coordination. The findings demonstrate that sustainable work-zone safety requires an integrated socio-technical approach combining behavioral enforcement, adaptive TTC and ITTC management, structured inspection practices, and organizational accountability. The study provides practitioner-informed guidance for agencies and contractors to institutionalize ITTC within specifications, prioritize high-impact enforcement strategies, and adopt safety management frameworks shaped by field-tested professional expertise to address recurrent safety challenges in active construction environments.
