Authors,Author(s) ID,Title,Year,Source title,Volume,Issue,Art. No.,Page start,Page end,Page count,Cited by,DOI,Link,Affiliations,Authors with affiliations,Abstract,Author Keywords,Index Keywords,Molecular Sequence Numbers,Chemicals/CAS,Tradenames,Manufacturers,Funding Details,Funding Text 1,Funding Text 2,References,Correspondence Address,Editors,Sponsors,Publisher,Conference name,Conference date,Conference location,Conference code,ISSN,ISBN,CODEN,PubMed ID,Language of Original Document,Abbreviated Source Title,Document Type,Publication Stage,Open Access,Source,EID
"Jeong S., Hou R., Lynch J.P., Sohn H., Law K.H.","56893042300;57190580657;7403674374;7201426396;55671078700;","An information modeling framework for bridge monitoring",2017,"Advances in Engineering Software","114",,,"11","31",,54,"10.1016/j.advengsoft.2017.05.009","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019995271&doi=10.1016%2fj.advengsoft.2017.05.009&partnerID=40&md5=b81eda4ea474eff91bfb1ce783057d61","Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States; Department of Civil and Environmental Engineering, University of Michigan, 2350 Hayward St., Ann Arbor, MI  48109-2125, United States; Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States","Jeong, S., Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States; Hou, R., Department of Civil and Environmental Engineering, University of Michigan, 2350 Hayward St., Ann Arbor, MI  48109-2125, United States; Lynch, J.P., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States; Sohn, H., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon  305-701, United States; Law, K.H., Department of Civil and Environmental Engineering, Stanford University, 473 Via Ortega, Stanford, CA  94305-4020, United States","Bridge management involves a variety of information from different data sources, including geometric model, analysis model, bridge management system (BMS) and structural health monitoring (SHM) system. Current practice of bridge management typically handles these diverse types of data using isolated systems and operates with limited use of the data. Sharing and integration of such information would facilitate meaningful use of the information and improve bridge management, as well as enhance bridge operation and maintenance and public safety. In many industries, information models and interoperability standards have been developed and employed to facilitate information sharing and collaboration. Given the success of building information modeling (BIM) in the Architecture, Engineering and Construction (AEC) industry, efforts have been initiated to develop frameworks and standards for bridge information modeling (BrIM). Current developments of BrIM focus primarily on the physical descriptions of bridge structures, such as geometry and material properties. This paper presents an information modeling framework for supporting bridge monitoring applications. The framework augments and extends the prior work on the OpenBrIM standards to further capture the information relevant to engineering analysis and sensor network. Implementation of the framework employs an open-source NoSQL database system for scalability, flexibility and performance. The framework is demonstrated using bridge information and sensor data collected from the Telegraph Road Bridge located in Monroe, Michigan. The results show that the bridge information modeling framework can potentially facilitate the integration of information involved in bridge monitoring applications, and effectively support and provide services to retrieve and utilize the information. © 2017","Bridge information modeling; Bridge management; Bridge monitoring; NoSQL database","Architectural design; Information theory; Network function virtualization; Open systems; Sensor networks; Standards; Structural health monitoring; Architecture , engineering and construction industries; Bridge management; Bridge monitoring; Building Information Model - BIM; Information Modeling; Information modeling frameworks; Nosql database; Structural health monitoring (SHM); Information management",,,,,"ECCS-1446330; National Sleep Foundation, NSF; Michigan Department of Transportation, MDOT; Center for Social Inclusion, CSI; Stanford University, SU; University of Michigan, U-M; Ministry of Land, Infrastructure and Transport, MOLIT; Korea Agency for Infrastructure Technology Advancement, KAIA","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA). The research is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. Any opinions, findings, conclusions or recommendations expressed in this paper are solely those of the authors and do not necessarily reflect the views of NSF, MOLIT, MDOT, KAIA or any other organizations and collaborators.","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) . The research is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. Any opinions, findings, conclusions or recommendations expressed in this paper are solely those of the authors and do not necessarily reflect the views of NSF, MOLIT, MDOT, KAIA or any other organizations and collaborators.","Bartholomew, M., FHWA bridge information modeling update (2015), http://bridges.transportation.org/Documents/2015%20SCOBS%20presentations/Technical%20Committee/T-19-Mike%20Bartholomew-FHWA%20Bridge%20Information%20Modeling.pdf, [Online article], Retrieved from: (accessed on 20 April 2016); Bartholomew, M., Blasen, B., Koc, A., Bridge information modeling (BrIM) using open parametric objects (2015), Federal Highway Administration Report No. FHWA-HI F -16-010; Industry foundation classes version 4 - addendum 1 (2016), http://www.buildingsmart-tech.org/ifc/IFC4/Add1/html/, [Online article], Retrieved from:accessed on 20 May accessed on 20 May; Chen, S.S., Bridge data protocols for interoperability local failure bridge data protocols for interoperability and life cycle management (2013), http://iug.buildingsmart.org/resources/itm-and-iug-meetings-2013-munich/infra-room/bridge-data-protocols-for-interoperability-and-life-cycle-management, [Online article], Retrieved from: (accessed on 20 April 2016); Chen, S.S., Shirolé, A.M., Integration of information and automation technologies in bridge engineering and management: extending the state of the art (2006) Transp Res Rec, 1976 (1), pp. 3-12; Chen, S.S., Shirolé, A.M., Implementation roadmap for bridge information modeling (BrIM) data exchange protocols (2013), SubTask 12.2 Multi-Year Implementation Roadmap Revised Draft documenting updates to July 2013; Structural bridge design software | CSiBridge (2016), https://www.csiamerica.com/products/csibridge, [Online article], Retrieved from:accessed on 20 April accessed on 20 April; Introduction to cassandra query language (2016), http://docs.datastax.com/en/cql/3.1/cql/cql_intro_c.html, [Online article], Retrieved from:(accessed on 20 April (accessed on 20 April; Getting started with time series data modeling (2016), https://academy.datastax.com/demos/getting-started-time-series-data-modeling, [Online article], Retrieved from:accessed on 20 April accessed on 20 April; Python Cassandra Driver (2016), https://datastax.github.io/python-driver/, [Online article], Retrieved from:accessed on 20 April accessed on 20 April; Eastman, C.M., Building product models: computer environments, supporting design and construction (1999), CRC press; Eastman, C., Teicholz, P., Sacks, R., Liston, K., BIM handbook: a guide to building information modeling for owners, managers, designers, engineers, and contractors (2011), John Wiley & Sons, Inc Hoboken, NJ; Gazoni, E., Clark, C., openpyxl - a python library to read/write excel 2010 xlsx/xlsm files (2016), http://openpyxl.readthedocs.org/en/default/, [Online article], Retrieved from (accessed on 20 April 2016); Grolinger, K., Higashino, W.A., Tiwari, A., Capretz, M.A., Data management in cloud environments: NoSQL and NewSQL data stores (2013) J Cloud Comput, 2 (1), pp. 22-41; Hecht, R., Jablonski, S., NoSQL evaluation: a use case oriented survey (2011) Proceedings of CSC 2011, pp. 336-341; Hewitt, E., Cassandra: the definitive guide (2010), http://proquest.safaribooksonline.com/9781449399764, O'Reilly Media, Inc. [Safari Book Online], Retrieved from: (accessed on 20 April 2016); Hou, R., Zhang, Y., O'Connor, S., Hong, Y., Lynch, J.P., Monitoring and identification of vehicle-bridge interaction using mobile truck-based wireless sensors (2015) Proceedings of 11th international workshop on advanced smart materials and smart structures technology, august 1-2, 2015, , University of Illinois Urbana-Champaign, United States; ISO 10303:1994 – industrial automation systems and integration – product data representation and exchange (1994), International Organization for Standardization (ISO) Geneva, Switzerland; ISO 10303-104:2000 – Industrial automation systems and integration – product data representation and exchange – part 104: integrated application resource: finite element analysis (2000), International Organization for Standardization (ISO) Geneva, Switzerland; Jeong, S., Zhang, Y., O'Connor, S.M., Lynch, J.P., Sohn, H., Law, K.H., A NoSQL data management infrastructure for bridge monitoring (2016) Smart Struct Syst, 17 (4), pp. 669-690; Lakshman, A., Malik, P., Cassandra: a decentralized structured storage system (2010) Oper Syst Rev (ACM), 44 (2), pp. 35-40; Lee, K., IEEE 1451: a standard in support of smart transducer networking (2000) Proceedings of IEEE instrumentation and measurement technology conference, 2, pp. 525-528; Lee, S.-H., Jeong, Y.-S., A system integration framework through development of ISO 10303-based product model for steel bridges (2006) Automation Constr, 15 (2), pp. 212-228; Li, H., Ou, J., Zhao, X., Zhou, W., Li, H., Zhou, Z., Structural health monitoring system for the Shandong Binzhou yellow river highway bridge (2006) Comput-Aided Civil Infrastructure Eng, 21 (4), pp. 306-317; Li, Y., Manoharan, S., A performance comparison of SQL and NoSQL databases (2013) Proceedings of IEEE Pacific RIM conference on communications, computers, and signal processing, pp. 15-19. , art. no. 6625441; Marzouk, M.M., Hisham, M., Bridge information modeling in sustainable bridge management (2011) Proceedings of the international conference on sustainable design and construction 2011: integrating sustainability practices in the construction industry, pp. 457-466; Nagel, R.N., Braithwaite, W.W., Kennicott, P.R., Initial graphics exchange specification IGES version 1.0 (1980) NBSIR, pp. 80-1978. , Washington DC: National Bureau of Standards; OGC® SensorML: model and XML encoding standard (2014), http://www.opengeospatial.org/standards/sensorml, [Online article], Retrieved from: (accessed on 20 April 2016; OpenBrIM V3 (2016), https://openbrim.appspot.com/schema.xsd?for=openbrim&v=3&format=xsd&version&1.1, [Online resource], Retrieved from:accessed on 10 November accessed on 10 November; Param, M.L., ParamML author's guide (2016), https://sites.google.com/a/redeqn.com/paramml-author-s-guide/system/app/pages/recentChanges, [Online article], Retrieved from:accessed on 20 April accessed on 20 April; Pschorr, J., Henson, C.A., Patni, H.K., Sheth, A.P., Sensor discovery on linked data (2010), http://corescholar.libraries.wright.edu/knoesis/780, Retrieved from: (accessed 2 March, 2016; 19.7. xml.etree.ElementTree - the ElementTree XML API (2016), https://docs.python.org/2/library/xml.etree.elementtree.html, [Online article], Retrieved from:accessed on 20 April accessed on 20 April; pywin32 214: python package index (2016), https://pypi.python.org/pypi/pywin32, [Online article], Retrieved from:accessed on 7 October accessed on 7 October; 7.5. StringIO — read and write strings as files (2016), https://docs.python.org/2/library/stringio.html, [Online article], Retrieved from:accessed on 7 October accessed on 7 October; Robert, W.E., Marshall, A.R., Shepard, R., Aldayuz, J., The Pontis bridge management system: state-of-the-practice in implementation and development (2003) Proceedings of the 9th international bridge management conference, pp. 49-60; Samec, V., Stamper, J., Sorsky, H., Gilmore, T.W., Long span suspension bridges – bridge information modeling (2014) Proceedings of 7th international conference of bridge maintenance, safety and management, pp. 1005-1010; Stonebraker, M., Madden, S., Abadi, D.J., Harizopoulos, S., Hachem, N., Helland, P., The end of an architectural era (it's time for a complete rewrite) (2007) Proceedings of the 33rd international conference on very large data bases, pp. 1150-1160; Wang, L., Tang, A., Cui, Y., Yang, S., Zhan, Z., Study on the development of sihui bridge management system (2009) Proceedings of 2009 WRI World Congress on software engineering, pp. 487-491. , IEEE; Yabuki, N., Lebegue, E., Gual, J., Shitani, T., International collaboration for developing the bridge product model IFC-Bridge (2006) Proceeding of the 11th international conference on computing in civil and building engineering, pp. 1927-1936; Zhang, Y., O'Connor, S.M., van der Linden, G., Prakash, A., Lynch, J.P., SenStore: a scalable cyberinfrastructure platform for implementation of Data-to-Decision frameworks for infrastructure health management (2016) J Comput Civ Eng; Zhou, H.F., Chan, T.K., Wang, J.Y., Ni, Y.Q., A structural health monitoring data management system for instrumented cable-supported bridges (2006) Proceedings of the Asia-Pacific workshop on structural health monitoring, pp. 514-522","Jeong, S.; Department of Civil and Environmental Engineering, 473 Via Ortega, United States; email: swjeong3@stanford.edu",,,"Elsevier Ltd",,,,,09659978,,AESOD,,"English","Adv Eng Software",Article,"Final","",Scopus,2-s2.0-85019995271
"Perry B.J., Guo Y., Atadero R., van de Lindt J.W.","57217167354;55873076900;23988525500;6701580121;","Streamlined bridge inspection system utilizing unmanned aerial vehicles (UAVs) and machine learning",2020,"Measurement: Journal of the International Measurement Confederation","164",,"108048","","",,34,"10.1016/j.measurement.2020.108048","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086581119&doi=10.1016%2fj.measurement.2020.108048&partnerID=40&md5=51819f50aefaf65ff84fb62e02f9dec6","Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States","Perry, B.J., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; Guo, Y., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; Atadero, R., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States; van de Lindt, J.W., Department of Civil and Environmental Engineering, Colorado State UniversityCO, United States","Recently, the rapid development of commercial unmanned aerial vehicles (UAVs) has made collecting images of bridge conditions trivial. Measuring the damage extent, growth, and location from the collected big image set, however, can be cumbersome. This paper proposes a streamlined bridge inspection system that offers advanced data analytics tools to automatically: (1) identify type, extent, growth, and 3D location of defects using computer vision techniques; (2) generate a 3D point-cloud model and segment structural elements using human-in-the-loop machine learning; and (3) establish a georeferenced element-wise as-built bridge information model to document and visualize damage information. This system allows bridge managers to better leverage UAV technologies in bridge inspection and conveniently monitor the health of a bridge through quantifying and visualizing the progression of damage for each structural element. The efficacy of the system is demonstrated using two bridges. © 2020 Elsevier Ltd","Bridge Information Model (BrIM); Bridge inspection; Computer vision; Machine learning; Structural Health Monitoring (SHM); Unmanned Aerial Vehicles (UAVs)","Advanced Analytics; Antennas; Bridges; Commercial vehicles; Composite structures; Data Analytics; Inspection; Inspection equipment; Machine learning; 3d point cloud models; Analytics tools; Bridge inspection; Computer vision techniques; Damage information; Human-in-the-loop; Information Modeling; Structural elements; Unmanned aerial vehicles (UAV)",,,,,"69A3551747108; U.S. Department of Transportation, DOT; Colorado State University, CSU; Mountain-Plains Consortium, MPC","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University’s Drone Center for providing the UAVs and support, as well as Dr. Ross Beveridge of Colorado State University for his insight on the project.","The work presented in this paper was conducted with support from Colorado State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation (FASTACT Grant No. 69A3551747108). The contents of this paper reflect the views of the authors, who are responsible for the facts and accuracy of the information presented. Additionally, the authors would like to acknowledge the Colorado State University's Drone Center for providing the UAVs and support, as well as Dr. Ross Beveridge of Colorado State University for his insight on the project.","Ryan, T.W., Mann, E., Chill, Z.M., Ott, B.T., Bridge Inspector's Reference Manual (2012), Federal Highway Administration Washington, D.C; (2018), AASHTO, The Manual for Bridge Evaluation, Third Edition, 2017, American Association of State Highway and Transportation Officials, Washington, D.C; Omar, T., Nehdi, M.L., Remote sensing of concrete bridge decks using unmanned aerial vehicle infrared thermography (2017) Autom. Constr., 83, pp. 360-371; Moore, M., Phares, B., Graybeal, B., Rolander, D., Washer, G., (2001), Reliability of Visual Inspection for Highway Bridges, Volume I: Final Report, Tech. rep., Federal Highway Administration, McLean, VA; Wells, J., Lovelace, B., (2017), Unmanned Aircraft System Bridge Inspection Demonstration Project Phase II Final Report, Tech. rep., Minnesota Department of Transportation, St. Paul, MN; Hernandez, I., Fields, T., Kevern, J., Overcoming the challenges of using unmanned aircraft for bridge inspections (2016) AIAA Atmospheric Flight Mechanics Conference, pp. 1-15. , American Institute of Aeronautics and Astronautics Reston, Virginia; Gillins, D.T., Parrish, C., Gillins, M.N., Simpson, C., (2018), Eyes in the Sky: Bridge Inspections With Unmanned Aerial Vehicles, Tech. rep., Oregon Department of Transportation, Salem, OR; Wells, J., Lovelace, B., (2018), Improving the Quality of Bridge Inspections Using Unmanned Aircraft Systems (UAS), Tech. rep., Minnesota Department of Transportation, St. Paul, MN; Duque, L., Seo, J., Wacker, J., Bridge deterioration quantification protocol using UAV (2018) J. Bridge Eng., 23, p. 04018080; Xu, Y., Turkan, Y., Br IM and UAS for bridge inspections and management, Engineering (2019) Constr. Architect. Manage., pp. 1-23. , in-press; Ye, X., Ni, Y., Wai, T., Wong, K., Zhang, X., Xu, F., A vision-based system for dynamic displacement measurement of long-span bridges: Algorithm and verification (2013) Smart Struct. Syst., 12, pp. 363-379; Ye, X., Dong, C.-Z., Liu, T., Image-based structural dynamic displacement measurement using different multi-object tracking algorithms (2016) Smart Struct. Syst., 17, pp. 935-956; Ye, X., Yi, T.-H., Dong, C., Liu, T., Vision-based structural displacement measurement: System performance evaluation and influence factor analysis (2016) Measurement, 88, pp. 372-384; Ye, X., Yi, T.-H., Dong, C., Liu, T., Bai, H., Multi-point displacement monitoring of bridges using a vision-based approach (2015) Wind Struct., 20, pp. 315-326; Jahanshahi, M.R., Masri, S.F., Adaptive vision-based crack detection using 3D scene reconstruction for condition assessment of structures (2012) Autom. Constr., 22, pp. 567-576; Talab, A.M.A., Huang, Z., Xi, F., HaiMing, L., Detection crack in image using Otsu's method and multiple filtering in image processing techniques (2016) Optik, 127, pp. 1030-1033; Reddy, A., Indragandhi, V., Ravi, L., Subramaniyaswamy, V., Detection of Cracks and damage in wind turbine blades using artificial intelligence-based image analytics (2019) Measurement, 147, p. 106823; Mitra, N.J., Nguyen, A., Estimating surface normals in noisy point cloud data (2003), pp. 322-328. , doi:10.1145/777792.777840. Proceedings of the Nineteenth Annual Symposium on Computational Geometry, Association for Computing Machinery, San Diego, CA; Lu, R., Brilakis, I., Middleton, C.R., Detection of structural components in point clouds of existing RC bridges (2019) Comput.-Aided Civil Infrastruct. Eng., 34, pp. 191-212; Czerniawski, T., Sankaran, B., Nahangi, M., Haas, C., Leite, F., 6D DBSCAN-based segmentation of building point clouds for planar object classification (2018) Autom. Constr., 88, pp. 44-58; Macher, H., Landes, T., Grussenmeyer, P., From point clouds to building information models: 3D semi-automatic reconstruction of indoors of existing buildings (2017) J. Appl. Sci., 7, p. 1030; Maalek, R., Lichti, D., Ruwanpura, J., Robust segmentation of planar and linear features of terrestrial laser scanner point clouds acquired from construction sites (2018) Sensors, 18, p. 819; Diaz-Vilarino, L., Gonzalez-Jorge, H., Martinez-Sanchez, J., Lorenzo, H., Automatic LiDAR-based lighting inventory in buildings (2015) Measurement, 73, pp. 544-550; Chiu, W., Ong, W., Kuen, T., Courtney, F., Large structures monitoring using unmanned aerial vehicles (2017) Proc. Eng., 188, pp. 415-423; Phung, M.D., Quach, C.H., Dinh, T.H., Ha, Q., Enhanced discrete particle swarm optimization path planning for UAV vision-based surface inspection (2017) Autom. Constr., 81, pp. 25-33; Jeong, G.Y., Nguyen, T.N., Tran, D.K., Hoang, T.B.H., Applying unmanned aerial vehicle photogrammetry for measuring dimension of structural elements in traditional timber building (2020) Measurement, 153, p. 107386; Lato, M.J., Gauthier, D., Hutchinson, D.J., Rock slopes asset management: selecting the optimal three-dimensional remote sensing technology (2015), pp. 7-14. , doi:10.3141/2510-02. Transportation Research Record: Journal of the Transportation Research Board, Transportation Research Board, Washington D.C; Roca, D., Armesto, J., Lagüela, S., Díaz-Vilariño, L., LiDAR-equipped UAV for building information modelling (2014) Int. Arch. Photogram., Remote Sens. Spatial Inform. Sci., XL-5, pp. 523-527; Cawood, A.J., Bond, C.E., Howell, J.A., Butler, R.W., Totake, Y., LiDAR, UAV or compass-clinometer: accuracy, coverage and the effects on structural models (2017) J. Struct. Geol., 98, pp. 67-82; Carvajal-Ramirez, F., Navarro-Ortega, A.D., Aguera-Vega, F., Martinez-Carricondo, P., Mancini, F., Virtual reconstruction of damaged archaeological sites based on Unmanned Aerial Vehicle Photogrammetry and 3D modelling. Study case of a southeastern Iberia production area in the Bronze Age (2019) Measurement, 136, pp. 225-236; Diaz-Vilarino, L., Gonzalez-Jorge, H., Martinez-Sanchez, J., Bueno, M., Arias, P., Determining the limits of unmanned aerial photogrammetry for the evaluation of road runoff (2016) Measurement, 85, pp. 132-141; Jancosek, M., Pajdla, T., Multi-view reconstruction preserving weakly-supported surfaces (2011) Computer Vision and Pattern Recognition 2011, pp. 3121-3128. , The Institute of Electrical and Electronics Engineers Colorado Springs; Moulon, P., Monasse, P., Marlet, R., Adaptive structure from motion with a contrario model estimation (2013), pp. 257-270. , doi:10.1007/978-3-642-37447-0_20. Asian Conference on Computer Vision 2012, Asian Conference on Computer Vision 2012, Daejeon Korea; Lowe, D., Object recognition from local scale-invariant features (1999) Proceedings of the Seventh IEEE International Conference on Computer Vision, The Institute of Electrical and Electronics Engineers, Kerkyra, Greece, pp. 1150-1157; Muja, M., Lowe, D., (2009), pp. 331-340. , Fast approximate nearest neighbors with automatic algorithm configuration., in: VISAPP 2009 - Proceedings of the 4th International Conference on Computer Vision Theory and Applications, Springer, Lisboa, Portugal doi:10.5220/0001787803310340; Wu, C., Towards linear-time incremental structure from motion (2013), pp. 127-134. , doi:10.1109/3DV.2013.25. 2013 International Conference on 3D Vision, The Institute of Electrical and Electronics Engineers, Seattle, WA; Schonberger, J.L., Frahm, J.-M., (2016), pp. 4104-4113. , Structure-from-motion revisited, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition, The Institute of Electrical and Electronics Engineers, Las Vega, NV doi:10.1109/CVPR.2016.445; Kazhdan, M., Hoppe, H., Screened poisson surface reconstruction (2013) ACM Trans. Graph., 32, pp. 1-13; Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Duchesnay, E., (2011), Scikit-learn: Machine learning in Python, Journal of Machine Learning Research 12 2825–2830. URL jmlr.org/papers/v12/pedregosa11a; Sankarasrinivasan, S., Balasubramanian, E., Karthik, K., Chandrasekar, U., Gupta, R., Health monitoring of civil structures with integrated UAV and image processing system (2015) Proc. Comput. Sci., 54, pp. 508-515; Zhou, Q., Park, J., Koltun, V., (2018), Open3D: A modern library for 3D data processing, Computing Research Repository (CoRR) abs/1801.09847 1–6. doi:1801.09847; Li, J., Wong, H.-C., Lo, S.-L., Xin, Y., Multiple object detection by a deformable part-based model and an R-CNN (2018) IEEE Signal Process. Lett., 25, pp. 288-292; Dorafshan, S., Thomas, R.J., Maguire, M., Comparison of deep convolutional neural networks and edge detectors for image-based crack detection in concrete (2018) Constr. Build. Mater., 186, pp. 1031-1045; Nhat-Duc, H., Nguyen, Q.-L., Tran, V.-D., Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network (2018) Autom. Constr., 94, pp. 203-213; Ye, X., Jin, T., Yun, C., A review on deep learning-based structural health monitoring of civil infrastructures (2019) Smart Struct. Syst., 5, pp. 567-586; Bradski, G., The OpenCV library (2000) Dr. Dobb's Journal of Software Tools, 25, pp. 120-125. , doi:10031023693; Canny, J., A computational approach to edge detection (1986) IEEE Trans. Pattern Anal. Mach. Intell., 8, pp. 679-714; ASTM International, ASTM C496 Standard Test Method for Splitting Tensile Strength of Cylindrical Concrete Specimens (2017), American Society for Testing and Materials West Conshohocken, PA; (2018), American Society of Civil Engineering (ASCE), 2017 Infrastructure Report Card, A Comprehensive Assessment of America's Infrastructure, Tech. rep., ASCE, Reston, VA; McGuire, B., Atadero, R., Clevenger, C., Ozbek, M., Bridge information modeling for inspection and evaluation (2016) J. Bridge Eng., 21, p. 04015076; Armendariz, R.R., Bowman, M.D., Bridge Load Rating (Joint Transportation Research Program) (2018), Indiana Department of Transportation West Lafayette, IN","Guo, Y.; Department of Civil and Environmental Engineering, United States; email: yanlin.guo@colostate.edu",,,"Elsevier B.V.",,,,,02632241,,MSRMD,,"English","Meas J Int Meas Confed",Article,"Final","",Scopus,2-s2.0-85086581119
"Jeong S., Hou R., Lynch J.P., Sohn H., Law K.H.","56893042300;57190580657;57199678735;7201426396;55671078700;","A scalable cloud-based cyberinfrastructure platform for bridge monitoring",2019,"Structure and Infrastructure Engineering","15","1",,"82","102",,14,"10.1080/15732479.2018.1500617","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059017514&doi=10.1080%2f15732479.2018.1500617&partnerID=40&md5=cd0e352a0deadbf6c32af07cd77d8bce","Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States; Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea","Jeong, S., Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States; Hou, R., Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Lynch, J.P., Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, United States; Sohn, H., Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Law, K.H., Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, United States","Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of data. Appropriate use of cloud computing infrastructure can enhance the long-term deployment of a structural health monitoring (SHM) system which would incur significant amount of data of different types. This paper presents a cloud-based cyberinfrastructure platform designed to support bridge monitoring. The cyberinfrastructure platform enables scalable management of SHM data and facilitates effective information sharing and data utilisation. A cloud-based platform comprises of virtual machines, distributed database and web servers. The peer-to-peer distributed database architecture provides a scalable and fault-tolerant data management system. Platform-neutral web services designed in compliant with the Representational State Transfer (REST) standard enables easy access to the cloud resources and SHM data. For data interoperability, a bridge information model for bridge monitoring applications is adopted. For demonstration, the scalable cloud-based platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cloud-based cyberinfrastructure platform can effectively manage the sensor data and bridge information and facilitate efficient access of the data as well as the bridge monitoring software services. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.","bridge information modelling; bridge monitoring; Cloud computing; interoperability; scalability; web services","Cloud computing; Digital storage; Distributed database systems; Information theory; Internet of things; Interoperability; Monitoring; Peer to peer networks; Scalability; Structural health monitoring; Web services; Websites; Bridge monitoring; Cloud computing infrastructures; Data interoperability; Data management system; Information modelling; Internet of Things (IOT); Representational state transfer; Structural health monitoring (SHM); Information management",,,,,"National Science Foundation, NSF: CMMI-1362513, ECCS-1446330, ECCS-1446521; Michigan Department of Transportation, MDOT; Stanford University, SU; University of Michigan, U-M; Ministry of Land, Infrastructure and Transport, MOLIT; Korea Agency for Infrastructure Technology Advancement, KAIA","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) and is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan). The authors thank the Michigan Department of Transportation (MDOT) for access to the Telegraph Road Bridge, Newburg Road Bridge and for offering support during installation of the wireless monitoring system. The in-kind support by Computers and Structures, Inc. for providing the CSI Bridge software to the research team at Stanford University is gratefully appreciated. While certain commercial systems are identified in this paper, such identification does not imply recommendation or endorsement by the authors, NSF, MOLIT, MDOT or KAIA; nor does it imply that the products identified are necessarily the best available for the purpose. Furthermore, any opinions, findings, conclusions or recommendations expressed in this paper are solely those of the authors and do not necessarily reflect the views of NSF, MOLIT, MDOT, KAIA or any other organisations and collaborators.","This research is supported by a Grant No. 13SCIPA01 from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement (KAIA) and is also partially supported by a collaborative project funded by the US National Science Foundation (Grant No. ECCS-1446330 to Stanford University and Grant No. CMMI-1362513 and ECCS-1446521 to the University of Michigan).","Agrawal, D., Das, S., Abbadi, A.E., Big data and cloud computing: Current state and future opportunities (2011) Proceedings of the 14Th International Conference on Extending Database Technology (EDBT/ICDT '11), pp. 530-533. , New York, NY; Alampalli, S., Alampalli, S., Ettouney, M., Big data and high-performance analytics in structural health monitoring for bridge management (2016) Proceedings of the SPIE Smart Structures/Nde Conference, , Las Vegas, NV, March 20–24; Arumugam, R., Enti, V.R., Bingbing, L., Xiaojun, W., Baskaran, K., Kong, F.F., Kumar, A.S., Kit, G.W., DAvinCi: A cloud computing framework for service robots (2010) 2010 IEEE International Conference on Robotics and Automation, pp. 3084-3089. , Anchorage, AK; Bartholomew, M., Blasen, B., Koc, A., (2015) Bridge information modeling (BrIM) using open parametric objects, , (Report No. FHWA-HI F-16-010). Federal Highway Administration; Belqasmi, F., Singh, J., Melhem, S.Y.B., Glitho, R.H., Soap-based vs. restful web services: A case study for multimedia conferencing (2012) IEEE Internet Computing, 16 (4), pp. 54-63; Brownjohn, J.M.W., Zasso, A., Stephen, G.A., Severn, R.T., Analysis of experimental data from wind-induced response of a long span bridge (1995) Journal of Wind Engineering and Industrial Aerodynamics, 54, pp. 13-24. , &; Chaniotis, I.K., Kyriakou, K.I.D., Tselikas, N.D., Is Node.js a viable option for building modern web applications? A performance evaluation study (2015) Computing, 97 (10), pp. 1023-1044; Chen, S.S., Shirolé, A.M., (2013) Implementation roadmap for bridge information modelling (BrIM) data exchange protocols, , Federal Highway Administration; Cheng, C.P., (2009) SC Collaborator: A service oriented framework for construction supply chain collaboration and monitoring, , (PhD thesis). Stanford University, Stanford, California; Cross, E.J., Koo, K.Y., Brownjohn, J.M.W., Worden, K., Long-term monitoring and data analysis of the Tamar Bridge (2013) Mechanical Systems and Signal Processing, 35 (1), pp. 16-34; Das, M., Cheng, J.C.P., Kumar, S.S., Social BIMCloud: A distributed cloud-based BIM platform for object-based lifecycle information exchange (2015) Visualization in Engineering, 3 (8), pp. 1-20; DataStax Node.Js Driver for Apache Cassandra [programminglibrary] (2017) Retrieved From, , https://github.com/datastax/nodejs-driver; Deckler, G., (2016) Cloud vs. On-premises – Hard dollar costs [online article], , https://www.linkedin.com/pulse/cloud-vs-on-premises-hard-dollar-costs-greg-deckler/?trk=pulse_spock-articles, Retrieved from; Dervilis, N., Worden, K., Cross, E.J., On robust regression analysis as a means of exploring environmental and operational conditions for SHM data (2015) Journal of Sound and Vibration, 347, pp. 279-296; Eastman, C., Teicholz, P., Sacks, R., Liston, K., (2011) BIM handbook: A guide to building information modelling for owners, managers, designers, engineers, and contractors, , Hoboken, NJ: John Wiley & Sons Inc; Farrar, C.R., Cornwell, P.J., Doebling, S.W., Prime, M.B., (2000) Structural health monitoring studies of the Alamosa Canyon and I-40 bridges, , Los Alamos, New Mexico: Los Alamos National Lab; Fielding, R.T., (2000) Architectural styles and the design of network-based software architectures, , (PhD Thesis). University of California, Irvine, USA; Fielding, R., Gettys, J., Mogul, J., Frystyk, H., Masinter, L., Leach, P., Berners-Lee, T., (1999) Hypertext transfer protocol–HTTP/1.1, , (No. RFC 2616); Fraser, M., Elgamal, A., He, X., Conte, J.P., Sensor network for structural health monitoring of a highway bridge (2009) Journal of Computing in Civil Engineering, 24 (1), pp. 11-24; Gillis, T., (2015) Cost Wars: Data Center Vs. Public Cloud [Online Article], , https://www.forbes.com/sites/tomgillis/2015/09/02/cost-wars-data-center-vs-public-cloud/#60c91b11923f, Retrieved from, (accessed on 5December 2017); Grolinger, K., Higashino, W.A., Tiwari, A., Capretz, M.A., Data management in cloud environments: NoSQL and NewSQL data stores (2013) Journal of Cloud Computing: Advances, Systems and Applications, 2 (1), pp. 22-41; Guinard, D., Trifa, V., Wilde, E., A resource oriented architecture for the Web of Things (2010) 2010 Internet of Things (IOT), Tokyo, 2010, pp. 1-8; Haas, H., Brown, A., (2004) Web Services Glossary,’ W3C Working Group Note [online article], , https://www.w3.org/TR/ws-gloss/, Retrieved from; Hewitt, E., (2010) Cassandra: The definitive guide, , Sebastopol, CA: OReilly Media, Inc; Hou, R., Jeong, S., Law, K.H., Lynch, J.P., Camera-based triggering of bridge structure health monitoring systems using a cyber-physical system framework (2017) International Workshop on Structural Health Monitoring (IWSHM 2017), , Stanford University, Stanford, CA, USA September 12–14, 2017; Jeong, S., Zhang, Y., O'Connor, S.M., Lynch, J.P., Sohn, H., Law, K.H., A NoSQL Data Management Infrastructure for Bridge Monitoring (2016) Smart Structures and Systems, 17 (4), pp. 669-690; Jeong, S., Zhang, Y., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., A cloud based information repository for bridge monitoring applications (2016) Proceedings of the SPIE Smart Structures/Nde Conference, , Las Vegas, NV, March 20–24; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., Cloud-based cyber infrastructure for bridge monitoring (2016) Proceedings of the 14Th International Symposium on Structural Engineering (ISSE-14), , Beijing, China, October12–15; Jeong, S., Hou, R., Lynch, J.P., Sohn, H., Law, K.H., An information modelling framework for bridge monitoring (2017) Advances in Engineering Software, 114, pp. 11-31; Koo, K.Y., Battista, N.D., Brownjohn, J.M.W., SHM data management system using MySQL database with MATLAB and web interfaces (2011) In 5Th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-5), pp. 589-596. , Cancún, México; Law, K.H., Smarsly, K., Wang, Y., Sensor data management technologies for infrastructure asset management (2014) Sensor Technologies for Civil Infrastructures: Applications in Structural Health Monitoring, 2 (1), pp. 3-32. , M. L. Wang, J. P. Lynch, H. Sohn, Cambridge, UK, Woodhead Publishing; Law, K.H., Cheng, J.C.P., Fruchter, R., Sriram, R.D., Engineering applications of the cloud (2016) Encyclopedia of cloud computing, , Murugesan S., Bojanova I., (eds), Chichester, UK: John Wiley & Sons, &,. (Eds; Le, T.D., Kim, S.H., Nguyen, M.H., Kim, D., Shin, S.Y., Lee, K.E., da Rosa Righi, R., EPC information services with No-SQL datastore for the Internet of Things (2014) 2014 IEEE International Conference on RFID (IEEE RFID), pp. 47-54. , Orlando, FL; Lea, R., Blackstock, M., City Hub: A cloud-based IoT platform for smart cities (2014) In 2014 IEEE 6Th International Conference on Cloud Computing Technology and Science, pp. 799-804. , Singapore; Lei, K., Ma, Y., Tan, Z., Performance comparison and evaluation of web development technologies in PHP, Python, and Node.js (2014) In Proceedings of 2014 IEEE 17Th International Conference on Computational Science and Engineering (CSE), Chengdu, China, pp. 661-668; Li, H., Ou, J., Zhao, X., Zhou, W., Li, H., Zhou, Z., Yang, Y., Structural health monitoring system for the Shandong Binzhou Yellow River highway bridge (2006) Computer‐Aided Civil and Infrastructure Engineering, 21 (4), pp. 306-317; Liao, Y., Mollineaux, M., Hsu, R., Bartlett, R., Singla, A., Raja, A., Rajagopal, R., Snowfort: An open source wireless sensor network for data analytics in infrastructure and environmental monitoring (2014) IEEE Sensors Journal, 14 (12), pp. 4253-4263. , …; Lim, H.J., Sohn, H., Liu, P., Binding conditions for nonlinear ultrasonic generation unifying wave propagation and vibration (2014) Applied Physics Letters, 104 (21), p. 214103; Lin, W., Dou, W., Zhou, Z., Liu, C., A cloud-based framework for home-diagnosis service over big medical data (2015) Journal of Systems and Software, 102, pp. 192-206; Lynch, J.P., Loh, K.J., A summary review of wireless sensors and sensor networks for structural health monitoring (2006) Shock and Vibration Digest, 38 (2), pp. 91-130; Mell, P., Grance, T., The NIST definition of cloud computing—Recommendations of the National Institute of Standards and Technology (2011) NIST Special Publication 800-145, , Computer Science Division, Information Technology Laboratory, National Institute of Standards; Mulligan, G., Gracanin, D., A comparison of SOAP and REST implementations of a service based interaction independence middleware framework (2009) Proceedings of the 2009 Winter Simulation Conference (WSC), pp. 1423-1432. , Austin, TX; O'connor, S.M., Lynch, J.P., Ettouney, M., Vander Linden, G., Alampalli, S., Cyber-enabled decision making system for bridge management using wireless monitoring systems: Telegraph Road Bridge demonstration project (2012) Proceedings of the NDE/NDT for Highways and Bridges: Structural Materials Technology Conference, 2012, pp. 177-184. , New York, NY; O’Connor, S.M., Zhang, Y., Lynch, J.P., Ettouney, M.M., Jansson, P.O., Long-term performance assessment of the telegraph road bridge using a permanent wireless monitoring system and automated statistical process control analytics (2017) Structure and Infrastructure Engineering, 13 (5), pp. 604-624; Overschee, P.V., (2002) Subspace Identification for Linear Systems [Matlab Package], , http://www.mathworks.com/matlabcentral/fileexchange/2290-subspace-identification-for-linear-systems, Retrieved from; (2014) OGC® Sensorml: Model and XML Encoding Standard [Online Article], , http://www.opengeospatial.org/standards/sensorml, Retrieved from; ParamML author's guide [online article] (2017) Retrieved From, , https://sites.google.com/a/redeqn.com/paramml-author-s-guide/; Pautasso, C., ‘BPEL for REST (2008) International Conference on Business Process Management, pp. 278-293; Pautasso, C., Alonso, G., The JOpera visual composition language (2005) Journal of Visual Languages and Computing, 16 (1-2), pp. 119-152; Pautasso, C., Zimmermann, O., Leymann, F., Restful web services vs. ‘Big’ web services: Making the right architectural decision (2008) Proceedings of the 17Th International Conference on World Wide Web, pp. 805-814. , Beijing, China, April 21–25; Pautasso, C., Composing RESTful Services with JOpera (2009) Proceeding of International Conference on Software, pp. 142-159. , Zurich, Switzerland; Rosenberg, F., Curbera, F., Duftler, M.J., Khalaf, R., Composing RESTful services and collaborative workflows: A lightweight approach (2008) IEEE Internet Computing, 12 (5), pp. 24-31; Sheng, Q.Z., Qiao, X., Vasilakos, A.V., Szabo, C., Bourne, S., Xu, X., Web services composition: A decade’s overview (2014) Information Sciences, 280, pp. 218-238; Smarsly, K., Law, K.H., Hartmann, D., Multiagent-based collaborative framework for a self-managing structural health monitoring system (2012) Journal of Computing in Civil Engineering, 26 (1), pp. 76-89; Smith, J.E., Nair, R., The architecture of virtual machines (2005) Computer, 38 (5), pp. 32-38; Stonebraker, M., Madden, S., Abadi, D.J., Harizopoulos, S., Hachem, N., Helland, P., The end of an architectural era (It's time for a complete rewrite) (2007) Proceedings of the 33Rd International Conference on Very Large Data Bases, Vienna, Austria, pp. 1150-1160; Strukhoff, R., (2017) Adopting an Iot Platform: Things to Know and Pitfalls to Avoid [Online Article], , https://www.altoros.com/blog/adopting-an-iot-platform-things-to-know-and-pitfalls-to-avoid/, Retrieved from; Swartz, R., Jung, D., Lynch, J.P., Wang, Y., Shi, D., Flynn, M.P., Design of a wireless sensor for scalable distributed in-network computation in a structural health monitoring system (2005) In 5Th International Workshop on Structural Health Monitoring (IWSHM), , Stanford, CA; (2014) XML Schema [Online Article], , https://www.w3.org/2001/XMLSchema, Retrieved from; Wong, K.Y., Lau, C.K., Flint, A.R., Planning and implementation of the structural health monitoring system for cable-supported bridges in Hong Kong (2000) Proceedings of the SPIE 3995. Nondestructive Evaluation of Highways, Utilities, and Pipelines IV; Xu, X., From cloud computing to cloud manufacturing (2012) Robotics and Computer-Integrated Manufacturing, 28 (1), pp. 75-86; Ye, X., Huang, J., A framework for cloud-based smart home (2011) Proceedings of 2011 International Conference on Computer Science and Network Technology, pp. 894-897. , Harbin; Zaslavsky, A., Perera, C., Georgakopoulos, D., Sensing as a service and big data (2013) International Conference on Advances in Cloud Computing (ACC-2012), pp. 21-29. , Bangalore, India, July; Zhang, Q., Cheng, L., Boutaba, R., Cloud computing: State-of-the-art and research challenges (2010) Journal of Internet Services and Applications, 1 (1), pp. 7-18; Zhang, Y., O’Connor, S.M., van Der Linden, G., Prakash, A., Lynch, J.P., SenStore: A scalable cyberinfrastructure platform for implementation of data-to-decision frameworks for infrastructure health management (2016) Journal of Computing in Civil Engineering, 30 (5); Zhou, G.D., Yi, T.H., Recent developments on wireless sensor networks technology for bridge health monitoring (2013) Mathematical Problems in Engineering 2013; Zhao, H., Doshi, P., Towards automated restful web service composition (2009) 2009 IEEE International Conference on Web Services, pp. 189-196. , Los Angeles, CA","Jeong, S.; Department of Civil and Environmental Engineering, United States; email: swjeong3@stanford.edu",,,"Taylor and Francis Ltd.",,,,,15732479,,,,"English","Struct. Infrastructure Eng.",Article,"Final","",Scopus,2-s2.0-85059017514
"Hajdin R.","6507346536;","Managing existing bridges - on the brink of an exciting future",2018,"Maintenance, Safety, Risk, Management and Life-Cycle Performance of Bridges - Proceedings of the 9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018",,,,"63","87",,6,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065289745&partnerID=40&md5=ab481f8ad8c47cdeccfc6e755e961933","Infrastructure Management Consultants GmbH, Zurich, Switzerland; Faculty of Civil Engineering, University of Belgrade","Hajdin, R., Infrastructure Management Consultants GmbH, Zurich, Switzerland, Faculty of Civil Engineering, University of Belgrade","It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition state, which is based upon observable damages recorded during inspections. Condition state is at best, only loosely correlated to safety and serviceability. It would be more reasonable to address safety and serviceability in inspection process directly, using the information on bridge performance obtained during the design and construction. The future Bridge Management Systems (fBMS) should therefore include this information allowing assessment of safety and serviceability based on inspection results. By including Bridge Information Models that are currently being developed and Structural Health Monitoring, the fBMS will become an invaluable decision-support tool not only for maintenance planning but also for issuing special permits, specification of heavy vehicle corridors, risk assessment due to natural hazards, etc. © 2018 Taylor & Francis Group, London, UK.","Bridges; Maintenance; Performance Indicators; Reliability; Safety; Service life; Serviceability","Accident prevention; Decision support systems; Health hazards; Health risks; Information management; Inspection; Life cycle; Maintenance; Reliability; Risk assessment; Service life; Structural health monitoring; Bridge management system; Bridge performance; Decision support tools; Design and construction; Inspection process; Maintenance planning; Performance indicators; Serviceability; Bridges",,,,,"Bundesanstalt für Straßenwesen, BASt: FE 15.0628/2016/LRB","This paper is partially based upon work supported by the German Federal Highway Research Institute under grant FE 15.0628/2016/LRB. Parts of paper address the work from COST Action TU-1406, Quality specifications for roadway bridges, standardization at a European level (BridgeSpec), supported by COST (European Cooperation in Science and Technology). The author is the leader of the Working Group 3 of the COST Action TU1406.",,"Adey, B., Hajdin, R., Methodology for determination of financial needs of gradually deteriorating bridges (2011) Journal of Structure and Infrastructure Engineering, 77 (8), pp. 645-660; Adey, B., Hajdin, R., Brühwiler, E., Supply and Demand System Approach to the Development of Bridge Management Strategies (2003) ASCE Journal of Infrastructure Systems, 3 (3), pp. 117-131; Adey, B., Hajdin, R., Van Linn, A., Welte, U., (2009) Effectiveness and Efficiency of Interventions on Highway Structures (In German), , Zurich: VSS, Report 625; Adey, B., Methodology and Base Cost Models to Determine the Total Benefits of Preservation Interventions and Road Sections in Switzerland (2012) Journal of Structure and Infrastructure Engineering, 8 (7), pp. 639-654; Alnaggar, M., Di Luzio, G., Cusatis, G., Modeling Time-Dependent Behavior of Concrete Affected by Alkali Silica Reaction in Variable Environmental Conditions (2017) Materials, 10 (5), p. 471; (2006) The Benefit of Transportation - Subproject: Contribution of Transportation to Value Creation in Switzerland (Der Nutzen Des Verkehrs - Teilprojekt: Beitrag Des Verkehrs Zur Wertschöpfung in Der Schweiz), , Bern: Federal Office for Spatial Development and Federal Roads Office; Management of natural hazards on NHS (In German: Management von Naturgefahren auf den Nationalstrassen), Guidelines (2014) Bern: Swiss Federal Roads Office; (2015) Phase Plan for Digital Planning and Constructing(Stufenplan Digitales Planen Und Bauen), , Berlin: Federal Ministry of Transport and Digital Infrastructure; Part 3: Analysis of existing road bridges due to special transports (2016) Provisions and Guidelines for Analysis and Diemsnioning of Structures (In German), , Bonn: Fedral Ministry of Transport and Digital Infrastructure; Bocchini, P., Frangopol, D.M., Ummenhofer, T., Zinke, T., Resilience and Sustainability of Civil Infrastructure: Toward a Unified Approach (2014) ASCE Journal of Infrastructure Systems, 20 (2); Braml, T., Wurzer, O., Probabilistic analysis methods as an additional component for the integrated assessment of existing bridges (In German) (2012) Beton-Und Stahlbetonbau, 10710, pp. 654-668; Bruneau, M., A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities (2003) Earthquake Spectra, 19 (4), pp. 733-752; (2018) Ifcstructuralanalysismodel, , http://www.buildingsmarttech.org/ifc/IFC2x3/TC1/html/ifcstructuralanalysisdomain/lexical/ifcstructuralanalysismodel.htm, [Zugriff am 02 01 2018]; Calgaro, J.-A., Sedlacek, G., (1992) EC1: Traffic Loads on Road Bridges, p. 65. , IABSE reports, Band; Caprani, C., Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification (2013) ASCE Journal of Bridge Engineering, 189, pp. 901-909; Cawley, P., Structural health monitoring: Closing the gap between research and industral development (2018) Structural Health Monitoring, pp. 1-20; Cen, E.N., (1990) 2002. Basis of Structural Design, , Brussels: European Committee for Standardisation; Chipman, T., Bridge Information Modeling Standardization (2016) Report No. FHWA-HIF-16-011, , Washington D. C.: FHWA; Das, P., Development of a comprehensive structures management methodology for the Highways Agency (1999) Management of Highway Structures, , London: ICE, Highways Agency; Enright, B., O'brien, E.J., Monte Carlo simulation of extreme traffic loading on short and medium span bridges (2013) Structure and Infrastructure Engineering, 912, pp. 1267-1282; Faber, M.H., (2009) Methodological Basis for Comparative Risk Assessment (In German), p. 618. , VSS, Report; Faber, M.H., Qin, J., Miraglia, S., Thöns, S., (2016) 2017. on the Probabilistic Characterization of Robustness and Resilience. Procedia Engineering,, 198, Special Issue, pp. 1070-1083. , Urban Transitions Conference, Shanghai; Freundt, U., Bönning, S., Traffic load models for recalculation of existing (Verkehrslastmodelle für die Nachrechnung von Straßenbrücken im Bestand) (2011) Bonn: Federal Highway Institute; Frischmann, B.M., Infrastructure - the social value of shared resources (2012) New York: Oxford University Press; Hajdin, R., Visual inspections and key performance indicators - Bridging the gap. Transportation Research Circular (2017) 11Th International Bridge and Structures Management Conference, , October, Issue E-C224; Hajdin, R., (2017) Bridge Resilience, , Zurich: IMC GmbH (unpublished manustript); Hajdin, R., Despot, Z., TRUCK - Bridge Rating Software (1999) International Bridge Management Conference, Denver, , Colorado, April 26-28, 1999. Washington D. C.: Transportation Research Board; Hajdin, R., Holst, R., Büchel, B., Rabe, R., A new practice-oriented approach for relibability-based bridge inspections (To be published) (2018) The Sixth International Symposium on Life-Cycle Civil Engineering; Hajdin, R., Peeters, L., Bridging Data Voids: Advanced Statistical Methods for Bridge Management in KUBA (2008) 10Th International Bridge and Structure Management Conference, Buffalo, New York, pp. 90-104. , TRB Circular E-C128, October; Heitzler, M., A Simulation and Visualization Environment for Spatiotemporal Disaster Risk Assessments of Network Infrastructures (2017) Cartographica: The International Journal for Geographic Information and Geovisualization, 52 (4), pp. 349-353; Hüthwohl, P., Brilakis, I., Borrmann, A., Sacks, R., Integrating RC Bridge Defect Information into BIM Models (2018) ASCE Journal of Computing in Civil Engineering, 32 (3). , 04018013; (2013) Probabilistic Model Code, , Lyngby: Joint Committee for Structural Safety; Kurte, J., Esser, K., Benefit of road traffic (Nu zen des Straßenverkehres) (2008) ADAC Study on Mobility (In German), , Munich: ADAC (Ed.); Lethanh, N., Hackl, J., Adey, B., Determination of Markov Transition Probabilities to be Used in Bridge Management from Mechanistic-Empirical Models (2017) ASCE Joournal of Bridge Engineering, 22 (10); Linneberg, P., Mašović, S., Hajdin, R., (2017) Quality Control Plans for Girder and Frame Bridges, , IABSE Symposium, Vancouver; Lou, P., Nassif, H., Truban, P., Development of live load model for strenght II limit state in AASHTO LRFD design specifications (2018) Transportation Reserach Board, Annual Meeting; Mandić Ivanković, A., Skokandić, D., Žnidarič, A., Kreslin, M., Bridge performance indicators based on traffic load monitoring (2017) Structure and Infrastructure Engineering, pp. 1-13; Mertz, D., (2005) Load Rating by Load and Resistance Factor Evaluation Method, , Washington D. C.: Transportation Research Board; Meystre, T., Hirt, M., (2006) Examination of Existing Road Bridges with Updated Road Loads (Überprpfung Bestehnder Strassenbrücken Mit Aktualisierten Strassenlasten), , Bern: Swiss Federal Roads Office; (1997) Concrete Details Vulnerability Manual, , Albany, NY: New York State Departement of Transportation; Padgett, J., Dennemann, K., Ghosh, J., Risk-based seismic life-cycle cost-benefit (LCC-B) analysis for bridge (2010) Structural Safety, 32 (3), pp. 165-173; Roelfstra, G., Hajdin, R., Adey, B., Brühwiler, E., Condition Evolution in Bridge Management Systems and Corrosion-Induced Deterioration (2004) ASCE Journal of Bridge Engineering, 9 (3), pp. 268-277; Schiffmann, F., Hajdin, R., (2017) Lont-Term Work Zone Planning for Highway Infrastructure. World Conference on Pavement and Asset Management, , WCPAM2017, June; (2011) SIA 269 - Maintenance of Existing Structures, , Zurich: Swiss Engineers and Architects Association; Tanasic, N., Hajdin, R., Management of Bridges with Shallow Foundations Exposed to Local Scour (2017) Journal of Structure and Infrastructure Engineering, Special Issue on IABMAS 2016; Treacy, M.A., Brühwiler, E., Are current bridge load modelling techniques realistic for existing road bridges? (2014) Bridge Maintenance, Safety, Management and Life Extension, 7Th International Conference on Bridge Maintenance, Safety and Management (IABMAS), pp. 340-347. , F. &. R. Chen, London: Taylor & Francis Group; (2015) Industry Snapshots: Uses of Transportation, , Wahsington D.C.: U.S. Departement of Transportation; (2003) Swiss Norm 640 904: Evaluation of Pavements, Road Structures and Equipment: Substance and Utilization Values, Zurich: Swiss Association of Road and Transport Experts, , https://en.wikipedia.org/wiki/6D_BIM, Wikipedia, 2017. 6D BIM., [Accessed 21 February 2018]","Hajdin, R.; Infrastructure Management Consultants GmbHSwitzerland","Powers N.Frangopol D.M.Al-Mahaidi R.Caprani C.","et al.;IABMAS, International Association for Bridge Maintenance and Safety;Monash University;RMIT University;Swinburne University of Technology;VicRoads","CRC Press/Balkema","9th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2018","9 July 2018 through 13 July 2018",,226219,,9781138730458,,,"English","Maint., Saf., Risk, Manag. Life-Cycle Perform. Bridges - Proc. Int. Conf. Bridge Maint., Saf. Manag.",Conference Paper,"Final","",Scopus,2-s2.0-85065289745
"Törmä S., Toivola P., Kiviniemi M., Puntila P., Lampi M., Mätäsniemi T.","6602149776;12782596400;6602426056;57215330840;55416083100;6504155486;","Ontology-based sharing of structural health monitoring data",2019,"20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report",,,,"2214","2221",,2,,"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074453225&partnerID=40&md5=f55afd0ddd1b66419b9819998cf10957","VisuaLynk, Espoo, Finland; Savcor Helsinki, Finland; VTT, Espoo, Finland; Trimble Solutions, Espoo, Finland; VTT, Tampere, Finland","Törmä, S., VisuaLynk, Espoo, Finland; Toivola, P., Savcor Helsinki, Finland; Kiviniemi, M., VTT, Espoo, Finland; Puntila, P., Trimble Solutions, Espoo, Finland; Lampi, M., Savcor Helsinki, Finland; Mätäsniemi, T., VTT, Tampere, Finland","A structural health monitoring system installed in a bridge produces a vast amount of sensor data that is analyzed and periodically reported to a bridge owner at an aggregate level. The data itself typically remains in the monitoring service of a service provider; it may be accessible to clients and third parties through a dedicated user interface and API. This paper presents an ontology to defining the monitoring model based on the Semantic Sensor Network Ontology by W3C. The goal is to enable an asset owner to utilize preferred tools to view and access monitoring data from different service providers, and in longer term, increase the utilization of monitoring data in facility management. The ultimate aim is to use BrIM as a digital twin of a bridge and to link external datasets to improve information management and maintenance over its lifecycle. © 20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report. All rights reserved.","Bridge information model; Facility management; Linked data; Monitoring; Ontology","Application programming interfaces (API); Information management; Life cycle; Linked data; Office buildings; Ontology; Semantics; Sensor networks; Structural health monitoring; User interfaces; Access monitoring; Different services; Facility management; Information Modeling; Monitoring models; Monitoring services; Service provider; Structural health monitoring systems; Monitoring",,,,,"City, University of London, City","This research belongs to a collaborative research project SmartBridgeFM (2017-2019), partially funded by Business Finland. Special thanks for City of Helsinki for providing the BrIMs of Crusell bridge.",,"Endsley, M.R., Toward a theory of situation awareness in dynamic systems (1995) Human Factors, 37 (1), pp. 85-104; W3C Data Activity, , https://www.w3.org/2013/data/, W3C; Dijkstra, E., On the role of scientific thought (1982) Selected Writings on Computing: A Personal Perspective, pp. 60-66. , NY, Springer; (2017) OPC Unified Architecture, , https://opcfoundation.org/ua/, OPC Foundation; Cyganiak, R., Wood, D., Lanthaler, M., (2014) RDF 1.1 Concepts and Abstract Syntax, W3C Recommendation, , https://www.w3.org/TR/rdf11-concepts/; (2012) OWL 2 Web Ontology LanguageDocument Overview, , https://www.w3.org/TR/owl-overview/, W3C Recommendation; Berners-Lee, T., (2006) Linked Data -Design Issues, W3C Note, , http://www.w3.org/DesignIssues/LinkedData.html; Linked Open Vocabularies, , https://lov.linkeddata.es/dataset/lov/; Törmä, S., Semantic linking of building information models (2013) IEEE Seventh International Conference on Semantic Computing, , Irvine, CA; Pauwels, P., Supporting decision-making in the building life-cycle using linked building data (2014) Buildings, 4 (3), pp. 549-579; Beetz, J., Van Leeuwen, J., De Vries, B., IFCOwl: A case of transforming EXPRESS schemas into ontologies (2009) AI EDAM, 23 (1), pp. 89-101; Pauwels, P., Terkaj, W., EXPRESS to OWL for construction industry: Towards a recommendable and usable ifcOWL ontology (2016) Automation in Construction, 63, pp. 100-133; Hoang, N.V., Törmä, S., Implementation and experiments with an IFC-to-linked data converter (2015) 32nd International Conference of CIB W78; Bonduel, M., Oraskari, J., Pauwels, P., Vergauwen, M., Klein, R., The IFC to linked building data converter - Current status (2018) 6th Linked Data in Architecture and Construction Workshop, , London; Haller, A., Janowicz, K., Cox, S., Le Phuoc, D., Taylor, K., Lefrançois, M., Semantic Sensor Network Ontology, W3C Recommendation, , https://www.w3.org/TR/vocab-ssn/, W3C; Cox, S., (2018) Extensions to the Semantic Sensor Network Ontology, , https://www.w3.org/TR/vocab-ssn-ext/, W3C; Turunen, M., Pulkkinen, P., Toivola, P., Structural health monitoring of Crusell bridge (2016) 19th IABSE Congress, , Stockholm; Crusell Bridge Trimble, , https://www.tekla.com/references/crusellbridge","Kiviniemi, M.; VTTFinland; email: markku.kiviniemi@vtt.fi",,"Allplan (Gala);et al.;Hardesty and Hanover;Silman;Wiss, Janney, Elstner Associates, Inc.;WSP","International Association for Bridge and Structural Engineering (IABSE)","20th IABSE Congress, New York City 2019: The Evolving Metropolis","4 September 2019 through 6 September 2019",,152767,,9783857481659,,,"English","Congr. IABSE, New York City: Evol. Metropolis - Rep.",Conference Paper,"Final","",Scopus,2-s2.0-85074453225
"Saju S.","57715573800;","Smart Bridges Based on Bridge Information Modelling",2022,"SPICES 2022 - IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems",,,,"279","284",,,"10.1109/SPICES52834.2022.9774179","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130927274&doi=10.1109%2fSPICES52834.2022.9774179&partnerID=40&md5=2838482df3283ad166f81588b44ed91d","Bridges Design Unit, Chief Design Office, Kerala Public Works Department, Trivandrum, India","Saju, S., Bridges Design Unit, Chief Design Office, Kerala Public Works Department, Trivandrum, India","Bridge structures are considered to be the very vulnerable part of civil transportation system that affect directly the public safety and economy. The maintenance of these bridges is many times disregarded in developing counties like India due to lack of maintenance fund, scarcity of experts to rectify problems and so many other reasons. Structural Health Monitoring (SHM) is a method for the diagnosis of damage based on periodically collected data from sensors placed on the structure that lead to characterize the damage and to maintain the health status of the structure. Sufficient expert knowledge is essential for an adequate solution of SHM tasks and Artificial Intelligence (AI) is now being focused on this tasks. Bridge Information Modelling (BrIM) is another digital application in bridge construction industry, which stores and updates the data beyond the design process, enabling engineers with relevant information to carryout fabrication, construction, and maintenance. In this paper a conceptual strategy to integrate the three digital techniques, SHM, AI and BrIM for developing smart bridges for smart cities is proposed. © 2022 IEEE.","AI; BIM; BrIM; SHM; Smart bridges","Architectural design; Bridges; Construction industry; Maintenance; Structural health monitoring; BIM; Bridge information modeling; Bridge structures; Civil transportation; Health status; Information Modeling; Maintenance funds; Public safety; Smart bridge; Transportation system; Information theory",,,,,,,,"Yan, R., Chen, X., Mukhopadhyay, S.C., (2017) Structural Health Monitoring, , Springer, Berlin, Germany; Garrett, J.H., Use of neural networks in detection of structural damage (1992) Computers and Structures, 42 (4). , Elsevier, Burlington, MA, USA; Bartholomew, M., Blasan, B., Koc, A., Bridge Information Modelling (BrIM) using Open Parametric Objects (2015) Report no. FHWA-HIF-16-010, Federal Highway Administration; Reitsema, A., Hordijk, D., Towards a SMART Bridge: A Bridge with Self-Monitoring, Analysing, and-Reporting Technologies (2015) Proceedings of the SMAR 2015: Third Conference on Smart Monitoring, Assessment & Rehabilitation of Civil Structures, pp. 16-19. , Antalya, Turkey October; Rizzo, P., Enshaeian, A., Bridge Health Monitoring in the United States: A Review (2021) Struct. Monit. Maint. Int. J., 8, pp. 1-50. , 2021; Catbas, F.N., Gul, M., Burkett, J.L., Damage assessment using flexibility and flexibility-based curvature for structural health monitoring (2007) SmartMater. Struct; Bazant, Z., Baweja, S., Short form of creep and shrink-age prediction model B3 for structures of medium sensitivity (1996) Mater. Struct, p. 587593; Zolghadri, N., Hailing, M.W., Barr, P.J., Foust, N., (2015) Effects of Temperature on Bridge Dynamic Properties, , Utah State University, Logan, UT, USA, Report no. CAIT-UTC-050; Li, Z.X., Chan, T.H.T., Ko, J.M., Fatigue analysis and life prediction of bridges with structural health monitoring data-Part I: Methodology and strategy (2001) Int. Journal of Fatigue, 23, pp. 45-53; Morris, W., Vico, A., Vazquez, M., De Sanchez, S., Corrosion of reinforcing steel evaluated by means of concrete resistivity measurements (2002) Corros. Set, 44, pp. 81-99; Hunt, B.E., Monitoring Scour Critical Bridges (2009) National Academies of Sciences, Engineering, andMedicine, , Washington, DC, 7X4; El-Tawil, S., Severino, E., Fonseca, P., Vehicle Collision with Bridge Piers (2005) Journal of Bridge Engineering, 10, pp. 345-353; Gonzalez, M.P., Zapico, J.L., Seismic damage identification in buildings using neural networks and modal data (2008) Comput. Struct, 86, pp. 416-426; Comisua, C., Taranub, N., Boacaa, G., Scutaru, M., Structural health monitoring system of bridges (2017) X International Conference on Structural Dynamics, EURODYN 201, , Elsevier, ProcediaEngineering","Saju, S.; Bridges Design Unit, India; email: sajus99@gmail.com",,"Mar Baselios College of Engineering and Technology - Autonomous (MBCETAA)","Institute of Electrical and Electronics Engineers Inc.","2022 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2022","10 March 2022 through 12 March 2022",,179344,,9781665449403,,,"English","SPICES - IEEE Int. Conf. Signal Process., Informatics, Commun. Energy Syst.",Conference Paper,"Final","",Scopus,2-s2.0-85130927274
"Polania D.R., Tondolo F., Osello A., Fonsati A., De Gaetani C., Trincianti C., Gazulli D.","57388547900;23668913100;55247387300;57203287238;55347405100;57304290000;57388305000;","Digitalization Processes and Bridge Information Modeling for Existing Bridges",2022,"Lecture Notes in Civil Engineering","200 LNCE",,,"944","953",,,"10.1007/978-3-030-91877-4_108","https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121915314&doi=10.1007%2f978-3-030-91877-4_108&partnerID=40&md5=27c680062e66337cd68af0dd4bb86ebc","Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy; S.C.R. Piemonte S.p.A., Corso Guglielmo Marconi 10, Turin, 10125, Italy; Lombardi Ingegneria S.r.l., Via Raimondo Montecuccoli 9, Turin, 10121, Italy","Polania, D.R., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Tondolo, F., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Osello, A., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; Fonsati, A., Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, 10129, Italy; De Gaetani, C., Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milan, 20133, Italy; Trincianti, C., S.C.R. Piemonte S.p.A., Corso Guglielmo Marconi 10, Turin, 10125, Italy; Gazulli, D., Lombardi Ingegneria S.r.l., Via Raimondo Montecuccoli 9, Turin, 10121, Italy","Bridges constant assessment, monitoring and retrofitting are key aspects to prevent inadequate damage situations. Considering the importance of these processes, a new official guideline for Bridge evaluation, classification and monitoring has been issued in Italy. The usage of BIM methodology comes as a logical solution to store and manage all information related to the bridge surveillance process and create a unique database. In the present work, HBIM methodologies are implemented for the creation of a damage database and new approaches are tested for the application of the guidelines directly on the BIM environment. Using the dismantled structures of Largo Grosseto bridge as a case study and damage information previously recovered as input data, HBIM models are created using two different methodologies: Parametric modelling and Mesh-to-BIM process. Moreover, the utility of the database created is expanded thanks to the usage of visual programming tools. The evaluation of the modelling processes highlights the effectiveness of BIM for infrastructure monitoring and classification. The results obtained demonstrate the way towards a new BIM monitoring standard procedure for infrastructure surveillance processes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.","Bridge inspection; HBIM; Structural Health Monitoring","Architectural design; Computer programming; Database systems; Structural health monitoring; Bridge evaluation; Bridge inspection; Bridge monitoring; Case-studies; Database approaches; Existing bridge; HBIM; Information Modeling; Logical solution; New approaches; Damage detection",,,,,"Allegheny Technologies Incorporated, ATI; Politecnico di Torino, POLITO; Politecnico di Milano; Regione Piemonte","BRIDGE|50 is a research project based on a research agreement among universities, public authorities, and private companies. Members of the Management Committee: S.C.R. Piemonte (President); Politecnico di Milano (Scientific Coordinator); Politecnico di Torino (Scientific Responsible of the Experimental Activities); Lombardi Engineering (Secretary); Piedmont Region; City of Turin; Metropolitan City of Turin; TNE Torino Nuova Economia; ATI Itinera & C.M.B.; ATI Despe & Perino Piero; Quaranta Group. BRIDGE|50 website: http://www. bridge50.org.",,"Song, G., Wang, C., Wang, B., Structural Health Monitoring (SHM) of civil structures (2017) Appl Sci, 7, p. 789. , https://doi.org/10.3390/app7080789; Lynch, J., Loh, K., A summary review of wireless sensors and sensor networks for structural health monitoring (2006) Shock Vib Dig, 38, pp. 91-128; (2020) Linee Guida per La Classificazione E Gestione Del Rischio, , la Valutazione della Sicurezza ed il Monitoraggio dei Ponti Esistenti, Rome, Italy; Shim, C., Yun, N., Song, H., Application of 3D bridge information modelling to design and construction of bridges (2011) Procedia Eng, 14, pp. 95-99; Yang, X., Yi-Chou, L., Murtiyoso, A., Koehl, M., Grussenmeyer, P., HBIM modeling from the surface mesh and its extended capability of knowledge representation (2019) ISPRS Int J Geo-Informat, 8 (7), p. 301. , https://doi.org/10.3390/ijgi8070301; Pocobelli, D.P., Boehm, J., Bryan, P., Still, J., Grau-Bové, J., Building information models for monitoring and simulation data in heritage buildings (2018) Int Archiv Photogrammet Remote Sens Spatial Inf Sci XLII, 2, pp. 909-916. , https://doi.org/10.5194/isprs-archives-XLII-2-909-2018; Simeone, D., Cursi, S., Toldo, I., Carrara, G., (2014) B(H)Im-Built Heritage Information Modelling; Rocha, G., Mateus, L., Fernández, J., Ferreira, V., A scan-to-BIM methodology applied to heritage buildings (2020) Heritage, 3, pp. 47-67. , https://doi.org/10.3390/heritage301000; Sun, Z., Zhang, Y., Using drones and 3D modelling to survey Tibetan architectural heritage: A case study with the multi-door stupa (2018) Sustainability, 10, p. 2259; Barazzetti, L., Banfi, F., Brumana, R., Previtali, M., Creation of parametric BIM objects from point clouds using nurbs (2015) Photogram Rec, 30, pp. 339-362; Santagati, C., Turco, M., Garozzo, R., Reverse information modelling for historic artefacts: Towards the definition of a level of accuracy for ruined heritage (2018) ISPRS – Int Archiv Photogrammet Remote Sens Spatial Inf Sci, 42-2, pp. 1007-1014; Yang, X., Koehl, M., Grussenmeyer, P., Mesh-To-BIM: From segmented mesh elements to BIM model with limited parameters (2018) ISPRS – Int Archiv Photogrammet Remote Sens Spatial Inf Sci, 42-2, pp. 1213-1218. , https://doi.org/10.5194/isprs-archives-XLII-2-1213-2018; Keviczky, L., Bars, R., Hetthéssy, J., Bányász, C., (2019) Case Study. Control Engineering: MAT-LAB Exercises. ATCSP, pp. 265-274. , https://doi.org/10.1007/978-981-10-8321-1_16, Springer, Singapore, pp; Boddupalli, C., Sadhu, A., Azar, E., Pattyson, S., Improved visualization of infrastructure monitoring data using building information modelling (2019) Struct Infrastruct Eng, 15, pp. 1-17. , https://doi.org/10.1080/15732479.2019.1602150; Barazzetti, L., Cloud-to-BIM-to-FEM: Structural simulation with accurate historic BIM from laser scans (2015) Simulat Model Pract Theory, 57, pp. 71-87. , https://doi.org/10.1016/j.simpat.2015.06.004; Zhao, Z., Integrating BIM and IoT for smart bridge management (2019) IOP Conf Ser Earth Environ Sci, 371. , https://doi.org/10.1088/1755-1315/371/2/022034; Biondini, F., BRIDGE|50 research project: Residual structural performance of a 50-year-old bridge (2021) Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020), 28 June–2 July 2020 (Postponed to 11–15 April, p. 2021. , Yokota H, Frangopol DM, Sapporo, Japan. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations. London: CRC Press, Taylor & Francis Group","Tondolo, F.; Politecnico di Torino, Corso Duca degli Abruzzi 24, Italy; email: D058687@polito.it","Pellegrino C.Faleschini F.Zanini M.A.Matos J.C.Casas J.R.Strauss A.",,"Springer Science and Business Media Deutschland GmbH","1st Conference of the European Association on Quality Control of Bridges and Structures, EUROSTRUCT 2021","29 August 2021 through 1 September 2021",,269849,23662557,9783030918767,,,"English","Lect. Notes Civ. Eng.",Conference Paper,"Final","",Scopus,2-s2.0-85121915314