## 6 Conclusions  
This work proposes a novel framework for automating the extraction, integration, and visualization of real-time weather data within digital twins, setting a new standard for environmental data-driven decision-making in construction management. Specifically, this study underscores the importance of integrating hazardous weather alerts into construction project decision-making, especially in the face of escalating climate change. Despite the value of timely weather information, such systems have been largely absent from BIM. To address this gap, an RPA-based protocol that automates the integration and visualization of weather data within BIM models is developed and validated in a real scenario. This approach not only streamlines the retrieval and processing of diverse weather data but also ensures timely digital alerts for hazardous conditions. The developed methodology also underscores the flexibility of BIM when integrated with other digital technologies, like RPA and parametric programming, showing the interoperability required for a seamless flow of information. By automating the extraction of weather data from multiple web-based sources and integrating it into BIM models, the study provides a practical tool for real-time hazard management, significantly reducing the manual effort required to monitor and update weather conditions. This not only increases operational efficiency but also mitigates the risk of human error--crucial in high-stakes environments where timely and accurate decision-making can prevent costly delays and improve safety outcomes. This research presents several limitations which represents challenges to be addressed in future research, such as:  
* Dependency on external data sources: The RPA's effectiveness relies heavily on the availability and accuracy of weather data from external websites. Changes in the data source's structure, such as updates to website layout or data format, could disrupt the extraction process and require adjustments to the RPA. To address this issue, the use of in situ sensors should be studied in future works;
* Software: The proposed application is currently restricted to Autodesk software, specifically Dynamo and Revit. To extend functionality to other BIM programs, a thorough examination of interoperability between different software platforms is necessary. This would involve revising both the parametric programming algorithms and the RPA protocol to accommodate diverse BIM environments;
* Scalability and adaptability: The application of the proposed methodology may face challenges when applied to different geographic locations or scales. Variations in local weather data sources, reporting standards, or project requirements could necessitate modifications to the RPA protocol to maintain functionality and accuracy;
* Maintenance and monitoring: Ongoing maintenance is crucial to ensure that the RPA performs effectively. This includes monitoring for updates or changes in the external websites, adjusting the protocol to handle new data formats, and ensuring compatibility with evolving versions of Dynamo and Revit. Finally, the study highlights the vast potential of RPA in the AEC industry, pointing to future opportunities to automate additional processes, integrate AI, and develop comprehensive RPA frameworks. This research aims to inspire a broader adoption of RPA technology in civil engineering, driving innovation and enhanced efficiency in the sector. Conceptualization, J.A.L.-G., E.A., F.M.-L.R. and F.L. ; methodology, J.A.L.-G., E.A., and F.M.-L.R. ; software, I.A., E.A. and F.L. ; validation, J.A.L.-G., E.A., and F.M.-L.R. ; formal analysis, J.A.L.-G., E.A., F.M.-L.R. and F.L. ; investigation, F.L. and I.A. ; resources, F.L. and I.A. ; writing--original draft preparation, F.L. ; writing--review and editing, J.A.L.-G., E.A., I.A. and F.M.-L.R. ; visualization, F.L., I.A. and E.A. ; supervision, J.A.L.-G., E.A. and F.M.-L.R. ; funding acquisition, J.A.L.-G. All authors have read and agreed to the published version of the manuscript.