Integrating Web-Based Weather Data into Building Information Modeling Models through Robot Process Automation
Source abstract
Abstract
The rapid evolution of digital technologies has revolutionized the architecture, engineering, and construction (AEC) industry, driving the wide-spread adoption of digital twins for structures. These virtual replicas, developed using Building Information Modeling (BIM) methodology, incorporate extensive information databases, proving indispensable for enhancing project management throughout a structure’s entire lifecycle and towards smart city development. As the impact of climate change continues to grow, hazardous weather alerts play a critical role as an early-warning system that notifies stakeholders of imminent threats, thereby influencing decision-making processes in construction projects. Surprisingly, despite its evident value, the integration of alert systems for hazardous weather conditions into BIM is often overlooked. To fill this gap, this paper proposes Robot Process Automation (RPA) protocols to automate the integration of real-time weather parameters into a structure’s BIM models. These very protocols are also used as alert systems, enabling the timely notification of stakeholders in the event of detected hazardous weather conditions. The effectiveness of the proposed methodology is demonstrated through its practical application in enhancing the safety of an actual building in Viña del Mar, Chile.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Process Automation Applications · Digital Transformation in Industry · BIM and Construction Integration
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering, Pontificia Universidad Católica de Valparaíso (PUCV), Valparaíso 2340000, Chile
Department of Civil and Environment Engineering, Universitat Politècnica de Catalunya (UPC), BarcelonaTech. C/Jordi Girona 1-3, 08034 Barcelona, Spain
Department of Civil Engineering, University of Castilla-La Mancha (UCLM), 13071 Ciudad Real, Spain
Funding
FEDER · Spanish Ministry of Economy and Competitiveness
References (100+)
Show source-provided references
1. BIM Methodology for Cost Analysis, Sustainability, and Management of Steel Structures with Reconfigurable Joints for Industrial Structures10.1016/j.jobe.2023.107443 ↗
2. Research on Unbalanced Mining of Highway Project Key Data Based on Knowledge Graph and Cloud Model10.1016/j.aej.2023.01.010 ↗
3. Amer, M., Naaman, A., M’Sirdi, N.K., and El-Zonkoly, A.M. (2014, January 26–27). Smart Home Energy Management Systems Survey. Proceedings of the International Conference on Renewable Energies for Developing Countries 2014, Beirut, Lebanon.10.1109/REDEC.2014.7038551 ↗
4. Automation in Construction Determining Building Information Modeling Effectiveness10.1016/j.autcon.2023.104861 ↗
5. Digital Twin Application in the Construction Industry: A Literature Review10.1016/j.jobe.2021.102726 ↗
6. Application of Building Information Modeling-Blockchain Integration in the Architecture, Engineering, and Construction/Facilities Management Industry: A Review10.1016/j.jobe.2023.107551 ↗
7. Automation in Construction Technologies for Digital Twin Applications in Construction10.1016/j.autcon.2023.104931 ↗
8. A Digital Twin Architecture for Real-Time and Offline High Granularity Analysis in Smart Buildings10.1016/j.scs.2023.104795 ↗
9. Developing a Novel Cash Flow Risk Analysis Framework for Construction Projects Based on 5D BIM10.1016/j.jobe.2021.103341 ↗
10. Lozano, F. (2024). Automatic Calibration and Sustainability Assessment of BIM Digital Twins with Smart Low-Cost Sensors Information. [Ph.D. Dissertation, Universidad de Castilla-La Mancha].
11. Automation in Construction Operations Planning and Scheduling in Off-Site Construction Supply Chain Management: Scope Definition and Future Directions10.1016/j.autcon.2023.104952 ↗
12. Greening Existing Buildings through Building Information Modelling: A Review of the Recent Development10.1016/j.buildenv.2021.107924 ↗
13. V How to Conduct Consistent Environmental, Economic, and Social Assessment during the Building Design Process. A BIM-Based Life Cycle Sustainability Assessment Method10.1016/j.jobe.2021.103516 ↗
14. A Review of Integration between BIM and CFD for Building Outdoor Environment Simulation10.1016/j.buildenv.2022.109862 ↗
15. Traffic Road Emission Estimation Through Visual Programming Algorithms and Building Information Models: A Case Study10.1109/ACCESS.2021.3123565 ↗
16. BIM-Based Fall Hazard Identification and Prevention in Construction Safety Planning10.1016/j.ssci.2014.08.001 ↗
17. Building Energy Consumption Optimization Method Based on Convolutional Neural Network and BIM10.1016/j.aej.2023.06.084 ↗
18. A Study of the Optimal Form and Orientation for More Energy Efficiency to Mass Model Multi-Storey Buildings of Kirkuk City, Iraq10.1016/j.aej.2023.03.020 ↗
19. (2023, September 18). Weather.Com. Available online: https://weather.com/weather/today/l/4494c890282e298d87b54d1ea711a4a05e54af783093a426fe8a4bfce11c306b98df80728f406b3a773c3bd6afebff2b.
20. (2023, September 28). AccuWeather. Available online: https://www.accuweather.com/es/es/barcelona/307297/weather-forecast/307297.
21. Seasonal Analysis of Thermal Comfort in Mediterranean Social Courtyards: A Comparative Study10.1016/j.jobe.2023.107756 ↗
22. Semantic Segmentation Recognition Model for Tornado-Induced Building Damage Based on Satellite Images10.1016/j.jobe.2022.105321 ↗
23. (2024, February 12). BBC Chile Forest Fires: More Than 100 Dead in Valparaíso Region. Available online: https://www.bbc.com/news/world-latin-america-68196048.
24. Automation in Construction BIM Compatibility and Its Differentiation with Interoperability Challenges as an Innovation Factor10.1016/j.autcon.2020.103086 ↗
25. State, P. (2022, October 07). Penn State BIM Uses. Available online: https://bim.psu.edu/uses/.
26. Rapid Deployment Modular Building Solutions and Climatic Adaptability: Case Based Study of a Novel Approach to “Thermal Capacity on Demand”10.1016/j.enbuild.2018.01.044 ↗
27. Surveying and Digital Workflow in Energy Performance Retrofit Projects Using Prefabricated Elements10.1016/j.autcon.2011.04.001 ↗
28. Prediction and Optimization of Thermal Comfort, IAQ and Energy Consumption of Typical Air-Conditioned Rooms Based on a Hybrid Prediction Model10.1016/j.buildenv.2022.109576 ↗
29. Compatibility of Existing Bim Maturity Models With Lean Construction and Integrated Project Delivery
30. (2023, October 09). Autodesk Energy Performance and Climate in BIM. Available online: https://www.autodesk.com/support/technical/article/caas/tsarticles/ts/1jpr14GEK6qUEyQgPzhIdr.html.
31. Mobaraki, B., Lozano-Galant, F., Soriano, R.P., and Castilla Pascual, F.J. (2021). Application of Low-Cost Sensors for Building Monitoring: A Systematic Literature Review. Buildings, 11.10.3390/buildings11080336 ↗
32. Dynamic Predicted Mean Vote: An IoT-BIM Integrated Approach for Indoor Thermal Comfort Optimization10.1016/j.autcon.2021.103805 ↗
33. A Receptive-Responsive Tool for Customizing Occupant’s Thermal Comfort and Maximizing Energy Efficiency by Blending BIM Data with Real-Time Information10.1108/SASBE-11-2020-0175 ↗
34. The Role of IoT Sensor in Smart Building Context for Indoor Fire Hazard Scenario: A Systematic Review of Interdisciplinary Articles10.1016/j.iot.2023.100803 ↗
35. Collao, J., Lozano-galant, F., and Lozano-galant, J.A. (2021). BIM Visual Programming Tools Applications in Infrastructure Projects: A State-of-the-Art Review. Appl. Sci., 11.10.3390/app11188343 ↗
36. Optimization of Geometric Parameters of Arch Bridges Using Visual Programming FEM Components and Genetic Algorithm10.1016/j.engstruct.2021.112465 ↗
37. Atencio, E., Araya, P., Oyarce, F., Herrera, R.F., Rivera, F.M., and Lozano-galant, F. (2022). Towards the Integration and Automation of the Design Process for Domestic Drinking-Water and Sewerage Systems with BIM. Appl. Sci., 12.10.3390/app12189063 ↗
38. BIM-Based Big Data Analytic System for Healthcare Facility Management10.1016/j.jobe.2022.105713 ↗
39. (2023, September 28). Integration of Environmental Sensors with BIM: Case Studies Using Arduino, Dynamo, and the Revit API. Available online: https://informesdelaconstruccion.revistas.csic.es/index.php/informesdelaconstruccion/article/view/3575/4027.
40. BIM-BVBS Integration with OpenBIM Standards for Automatic Prefabrication of Steel Reinforcement10.1016/j.autcon.2021.103654 ↗
41. Turning Robotic Process Automation into Commercial Success—Case OpusCapita10.1057/jittc.2016.5 ↗
42. A Systematic Literature Review on Intelligent Automation: Aligning Concepts from Theory, Practice, and Future Perspectives10.1016/j.aei.2021.101246 ↗
43. Atencio, E., Komarizadehasl, S., Lozano-Galant, J.A., and Aguilera, M. (2022). Using RPA for Performance Monitoring of Dynamic SHM Applications. Buildings, 12.10.3390/buildings12081140 ↗
44. Jiang, H., and Ling, R. (2022). Using RPA+BIM for High Efficient Operation of Smart Building’s Equipment Room. Preprint, 2022100045.10.20944/preprints202210.0045.v1 ↗
45. Robotic Process Automation: Contemporary Themes and Challenges10.1016/j.compind.2019.103162 ↗
46. Karn, S., and Kotecha, R. (2021). RPA-Based Implementation of IoT. SSRN Electron. J.10.2139/ssrn.3868873 ↗
47. Spark, W. (2023, October 24). Climate and Average Weather Year Round in Viña Del Mar. Available online: https://weatherspark.com/y/25809/Average-Weather-in-Viña-del-Mar-Chile-Year-Round.
48. Channel, T.W. (2023, October 24). Viña Del Mar Weather. Available online: https://weather.com/en-MT/weather/radar/interactive/l/6e23b2ba9a8b4e1124f4a09b2c1b01dc6a9e265569a816f505a0300fe40641a9.
49. (2023, October 24). Tiempo3 Pronóstico Del Tiempo Viña Del Mar. Available online: https://www.tiempo3.com/south-america/chile/valparaiso/vina-del-mar?page=today.
50. Windfinder (2023, October 24). Windfinder Weather Data. Available online: https://es.windfinder.com/forecast/vina_del_mar_valparaiso_chile.
51. Winckler, P., Contreras-López, M., Garreaud, R., and Meza, F. (2022). Analysis of Climate-Related Risks for Chile ’ s Coastal Settlements in the ARClim Web Platform. Water, 14.10.3390/w14223594 ↗
52. Martínez, C., Hidalgo, R., Henríquez, C., Arenas, F., Rangel-Buitrago, N., and Contreras-López, M. (2019). Nuevas Metodologías Para El Estudio de Marejadas En Chile. La Zona Costera en Chile: Adaptación y Planificación para la Resiliencia, CIGIDEN.
53. NOAA (2023, October 10). NOAA Satellites Track Blazing Wildfires in Chile, Available online: https://www.nesdis.noaa.gov/news/noaa-satellites-track-blazing-wildfires-chile.
54. Integrated Wildfire Danger Models and Factors: A Review10.1016/j.scitotenv.2023.165704 ↗
55. Hazard Risk Awareness and Disaster Management: Extracting the Information Content of Twitter Data10.1016/j.scs.2021.103577 ↗
56. (2024, February 12). X X: Happening Now. Available online: https://twitter.com/?lang=es.
57. Favari, E., and Cartoni, F. (2022). Towards the Integration Between Construction Projects and the Organization: The Connections Between BIM and Enterprise Architecture. Complexity and Sustainability in Megaprojects—MerIT, Springer.
58. Study on City Digital Twin Technologies for Sustainable Smart City Design: A Review and Bibliometric Analysis of Geographic Information System and Building Information Modeling Integration10.1016/j.scs.2022.104009 ↗
59. NASA (2010). DRAFT Modeling, Simulation, Information Technology & Processing Roadmap, NASA.
60. Digital Twin-Driven Manufacturing Equipment Development10.1016/j.rcim.2023.102557 ↗
61. An Intelligent Digital Twin System for Paper Manufacturing in the Paper Industry10.1016/j.eswa.2023.120614 ↗
62. Towards a Digital Twin Integrated DLT and IoT-Based Automated Healthcare Ecosystem
63. Using a Digital Twin to Explore Water Infrastructure Impacts during the COVID-19 Pandemic10.1016/j.scs.2021.103520 ↗
64. Interactive Real-Time Monitoring and Information Traceability for Complex Aircraft Assembly Field Based on Digital Twin10.1109/TII.2023.3234618 ↗
65. Key Technology of Digital Twin System for Aero-Engine Combustors
66. Rigorous Simulation of Geothermal Power Plants to Evaluate Environmental Performance of Alternative Configurations10.1016/j.renene.2023.03.038 ↗
67. Towards Electric Digital Twin Grid: Technology and Framework Review10.1016/j.egyai.2022.100213 ↗
68. Digital Twins for Automotive Development: Two Wheelers Application10.1016/j.aei.2023.101982 ↗
69. Li, Y., and Zhang, W. (2023). Traffic Flow Digital Twin Generation for Highway Scenario Based on Radar-Camera Paired Fusion. Sci. Rep., 13.10.1038/s41598-023-27696-z ↗
70. Cacciuttolo, C., Guzmán, V., Catriñir, P., Atencio, E., Komarizadehasl, S., and Lozano-Galant, J.A. (2023). Low-Cost Sensors Technologies for Monitoring Sustainability and Safety Issues in Mining Activities: Advances, Gaps, and Future Directions in the Digitalization for Smart Mining. Sensors, 23.10.3390/s23156846 ↗
71. Elbazi, N., Tigami, A., Laayati, O., El Maghraoui, A., Chebak, A., and Mabrouki, M. (2023, January 14–16). Digital Twin-Enabled Monitoring of Mining Haul Trucks with Expert System Integration: A Case Study in an Experimental Open-Pit Mine. Proceedings of the 2023 5th Global Power, Energy and Communication Conference (GPECOM), Nevsehir, Turkiye.10.1109/GPECOM58364.2023.10175789 ↗
72. Urban Digital Twin Challenges: A Systematic Review and Perspectives for Sustainable Smart Cities10.1016/j.scs.2023.104862 ↗
73. Favari, E., and Cantoni, F. (2022). Extended Reality (XR) as an Interaction Tool for Digital Twins: Application to Safety Management in Construction Megaprojects. International Workshop on A Multidisciplinary Approach to Embrace Complexity and Sustainability in Megaprojects, MERIT 2022, Springer.
74. Reduced-Order Digital Twin and Latent Data Assimilation for Global Wildfire Prediction10.5194/nhess-23-1755-2023 ↗
75. Kampczyk, A., and Dybeł, K. (2021). The Fundamental Approach of the Digital Twin Application in Railway Turnouts with Innovative Monitoring of Weather Conditions. Sensors, 21.10.3390/s21175757 ↗
76. Climate Change and Coastal Morphodynamics: Interactions on Regional Scales10.1016/j.scitotenv.2023.166432 ↗
77. Adade, D., and de Vries, W.T. (2023). Digital Twin for Active Stakeholder Participation in Land-Use Planning. Land, 12.10.3390/land12030538 ↗
78. (2023, September 02). Gartner Digital Twin Definition. Available online: https://www.gartner.com/en/information-technology/glossary/digital-twin#:~:text=Adigitaltwinisa,organization%2Cpersonorotherabstraction.
79. ScienceDirect Digital Digital Twin Twin in in Manufacturing: Manufacturing: A A Categorical Review Digital Twin in Review Classification10.1016/j.ifacol.2018.08.474 ↗
80. Robotics in Assembly-Based Industrialized Construction: A Narrative Review and a Look Forward10.1007/s41315-022-00257-9 ↗
81. Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study
82. Robotic Process Automation Implementation, Deployment Approaches and Success Factors—An Empirical Study
83. Importance of Process Flow and Logic Criteria for RPA Implementation10.1007/978-981-15-5764-4_20 ↗
84. Kong, X., and Falcone, F. (2020, January 27–29). Research on Intelligent Building Equipment Room Operation and Maintenance Platform Based on Digital Twins. Proceedings of the 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), Dalian, China.
85. Yamamoto, T., Hayama, H., Hayashi, T., and Mori, T. (2020). Automatic Energy-Saving Operations System Using Robotic Process Automation. Energies, 13.10.3390/en13092342 ↗
86. Construction of a Digital Twin Framework Using Free and Open-Source Software Programs
87. Everhard, J. (2023, September 02). The Pros and Cons of Citizen Development. Available online: https://www.forbes.com/sites/johneverhard/2019/01/22/the-pros-and-cons-of-citizen-development/?sh=4d04dfae84fd.
88. Xu, Z., Xie, Z., Wang, X., and Niu, M. (2022). Automatic Classification and Coding of Prefabricated Components Using IFC and the Random Forest Algorithm. Buildings, 12.10.3390/buildings12050688 ↗
89. Automation in Construction Benefits and Limitations of Using Low-Code Development to Support Digitalization in the Construction Industry10.1016/j.autcon.2023.104909 ↗
90. The Future Digital Work Force: Robotic Process Automation (RPA)
91. Van Chuong, L., Hung, P.D., and Diep, V.T. (2019, January 27–29). Robotic Process Automation and Opportunities for Vietnamese Market. Proceedings of the 7th International Conference on Computer and Communications Management, Bangkok, Thailand.10.1145/3348445.3348458 ↗
92. (2024, September 21). UiPath|Documentation. Available online: https://docs.uipath.com/es/activities/other/latest.
93. A Design Science Research Methodology for Information Systems Research10.2753/MIS0742-1222240302 ↗
94. Tiempo3.Com (2023, September 28). El Clima en Chile 2023|Chile 14 Días|Tiempo3.Com. Available online: https://www.tiempo3.com/south-america/chile.
95. (2023, September 28). Chile: Temperatura del Agua del mar Hoy y Pronósticos|TemperaturaDelMar.Es. Available online: https://www.temperaturadelmar.es/america-sur/chile/.
96. Diseño de Índices de Riesgo de Incendios Forestales Para Chile10.4206/bosque.1990.v11n2-06 ↗
97. Finkl, C.W., and Makowski, C. (2019). Beaufort Wind Scale. Encyclopedia of Coastal Science, Springer International Publishing.10.1007/978-3-319-93806-6 ↗
98. Álvarez, J.V., and Martinez, F.G. (2016). Marejadas Costa Afuera, Pronósticos de Oleaje Local y Cierres de Puerto. Proceedings of the VII Seminario Internacional de Ingeniería y Operación Portuaria, SOCHID.
99. (2023, September 28). UiPath AI-Powered Business Automation PlatformTM—Leader in RPA & Automation—UiPath. Available online: https://www.uipath.com/.
100. Automated Testing in Robotic Process Automation Projects