Applications of Augmented/Virtual Reality (AR/VR), Digital Twin, and Edge Computing in Smart Urban Resource Management, Waste Management, and Transportation

Abstract

The present study aimed to investigate the role of Augmented/Virtual Reality (AR/VR), Digital Twin systems, and Edge Computing in improving smart urban resource management, waste management optimization, intelligent transportation performance, environmental sustainability, and citizen satisfaction in Tehran. This study employed a mixed-methods exploratory-sequential design with qualitative and quantitative phases. In the qualitative stage, semi-structured interviews were conducted with 18 experts in smart city technologies, urban planning, transportation systems, environmental management, and digital infrastructure using purposive sampling until theoretical saturation was achieved. The qualitative findings were used to design a researcher-developed questionnaire containing 52 items distributed across dimensions including AR/VR applications, Digital Twin integration, Edge Computing efficiency, smart waste management, transportation performance, environmental sustainability, operational responsiveness, and citizen satisfaction. In the quantitative phase, 384 managers, urban planners, transportation experts, and municipal technology specialists from Tehran Municipality were selected through stratified random sampling. Content validity was confirmed through expert review, while construct validity was examined using exploratory and confirmatory factor analyses. Reliability coefficients exceeded 0.70 for all variables. Data were analyzed using SPSS-27 and AMOS-26 through descriptive statistics, Pearson correlation analysis, multiple regression, confirmatory factor analysis, and structural equation modeling. The results demonstrated significant positive relationships among all research variables at the 0.01 significance level. Digital Twin Integration had the strongest direct effect on Smart Urban Management Efficiency (β = 0.36, p = 0.001), followed by Edge Computing Efficiency (β = 0.33, p = 0.001) and AR/VR Applications (β = 0.29, p = 0.001). Smart Urban Management Efficiency significantly predicted Environmental Sustainability (β = 0.42, p = 0.001) and Citizen Satisfaction (β = 0.39, p = 0.001). The strongest correlation was observed between Edge Computing Efficiency and Operational Responsiveness (r = 0.78, p < 0.01). The structural equation model demonstrated acceptable fit indices (χ2/df = 2.11, RMSEA = 0.054, GFI = 0.93, AGFI = 0.91, CFI = 0.95, TLI = 0.94), confirming the adequacy of the proposed conceptual framework. The findings indicate that the integration of AR/VR technologies, Digital Twin systems, and Edge Computing infrastructures substantially enhances smart urban governance by improving operational efficiency, transportation management, waste management optimization, environmental sustainability, and citizen-centered service delivery. The study highlights the strategic importance of interoperable digital ecosystems and real-time intelligent infrastructures in supporting sustainable and resilient urban development in metropolitan environments.