PurposeDespite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deploy...
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PurposeDespite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC ***/methodology/approachA case study methodology was adopted, including individual case analyses and comparative multiple-case *** results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with "leveraging the diverse features of certain mature DT" being a shared recognition of all studied *** implicationsThis research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service ***/valueThis research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.
UAVs in most real-world deployments communicate with a ground control station either in a one-hop manner, which has a limited working range, or relies on infrastructure support such as satellite communication, which i...
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UAVs in most real-world deployments communicate with a ground control station either in a one-hop manner, which has a limited working range, or relies on infrastructure support such as satellite communication, which is expensive. Although multi-hop transmission is more economic, it is lossy and generally incurs large delays. In this paper, we consider a mixed method, where a few UAVs are equipped with satellite modules, and aggregate and forward traffic of nearby UAVs. The surrounding UAVs and the forwarding UAV form a star topology. Based on this model, we design an UAV formation strategy to cover a given region to minimize both the total number of UAVs and the number of UAVs with satellite modules. Since these two goals may be competing, we propose seven strategies and analyze them theoretically. Simulations show that a good tradeoff between the two goals can be obtained when each star network consists of four UAVs.
To construct circular barrier coverage (CBC) with multistatic radars, a deployment optimization method based on equipartition strategy is proposed in this paper. In the method, the whole circular area is divided into ...
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To construct circular barrier coverage (CBC) with multistatic radars, a deployment optimization method based on equipartition strategy is proposed in this paper. In the method, the whole circular area is divided into several sub-circles with equal width, and each sub-circle is blanketed by a sub-CBC that is built based on the multistatic radar deployment patterns. To determine the optimal deployment patterns for each sub-CBC, the optimization conditions are firstly studied. Then, to optimize the deployment of the whole circular area, a model based on minimum deployment cost is proposed, and the proposed model is divided into two sub-models to solve the optimization issue. In the inner model, it is assumed that the width of a sub-circle is given. Based on the optimization conditions of the deployment pattern, integer linear programming (ILP) and exhaustive method (EM) are jointly adopted to determine the types and numbers of deployment patterns. Moreover, a modified formula is introduced to calculate the maximum valid number of receivers in a pattern, thus narrowing the search scope of the EM. In the outer model, the width of a sub-circle is assumed to be a variable, and the EM is adopted to determine the minimum total deployment cost and the optimal deployment patterns on each sub-circle. Moreover, the improved formula is exploited to determine the range of width for a sub-circle barrier and reduce the search scope of the EM. Finally, simulations are conducted in different conditions to verify the effectiveness of the proposed method. The simulation results indicate that the proposed method can spend less deployment cost and deploy fewer transmitters than the state-of-the-artwork.
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