IoT Open-Source Architecture for the Maintenance of Building Facilities
Source abstract
Abstract
The introduction of the Internet of Things (IoT) in the construction industry is evolving facility maintenance (FM) towards predictive maintenance development. Predictive maintenance of building facilities requires continuously updated data on construction components to be acquired through integrated sensors. The main challenges in developing predictive maintenance tools for building facilities is IoT integration, IoT data visualization on the building 3D model and implementation of maintenance management system on the IoT and building information modeling (BIM). The current 3D building models do not fully interact with IoT building facilities data. Data integration in BIM is challenging. The research aims to integrate IoT alert systems with BIM models to monitor building facilities during the operational phase and to visualize building facilities’ conditions virtually. To provide efficient maintenance services for building facilities this research proposes an integration of a digital framework based on IoT and BIM platforms. Sensors applied in the building systems and IoT technology on a cloud platform with opensource tools and standards enable monitoring of real-time operation and detecting of different kinds of faults in case of malfunction or failure, therefore sending alerts to facility managers and operators. Proposed preventive maintenance methodology applied on a proof-of-concept heating, ventilation and air conditioning (HVAC) plant adopts open source IoT sensor networks. The results show that the integrated IoT and BIM dashboard framework and implemented building structures preventive maintenance methodology are applicable and promising. The automated system architecture of building facilities is intended to provide a reliable and practical tool for real-time data acquisition. Analysis and 3D visualization to support intelligent monitoring of the indoor condition in buildings will enable the facility managers to make faster and better decisions and to improve building facilities’ real time monitoring with fallouts on the maintenance timeliness.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: BIM and Construction Integration · 3D Surveying and Cultural Heritage · Advanced Manufacturing and Logistics Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Structural, Geotechnical and Building Engineering, Polytechnic of Turin, 10129 Turin, Italy
Department of Construction, Civil Engineering and Architecture, Marche Polytechnic University, 60121 Ancona, Italy
Department of Management and Production Engineering, Polytechnic of Turin, 10129 Turin, Italy
References (77)
Show source-provided references
1. Lauro, F., Moretti, F., Capozzoli, A., Khan, I., Pizzuti, S., Macas, M., and Panzieri, S. (2014, January 25–27). Building fan coil electric consumption analysis with fuzzy approaches for fault detection and diagnosis. Proceedings of the 2014 6th International Conference on Sustainability in Energy and Buildings, SEB-14, Energy Procedia 62, Cardiff, UK.10.1016/j.egypro.2014.12.403 ↗
2. Allen, P.A. (1986). An Integrated Power and Building Services Management System, INTELEC ’86, International Telecommunications Energy Conference, IEEE.10.1109/INTLEC.1986.4794478 ↗
3. Web Enabled Wireless Sensor Networks for Facilities Management10.1109/JSYST.2008.2007815 ↗
4. Pishdad-Bozorgi, P., Gao, X., Eastman, C., and Self, A.P. (2018). Planning and Developing Facility Management-Enabled Building Information Model (FM-enabled BIM), Automation in Construction, Elsevier.10.1016/j.autcon.2017.12.004 ↗
5. Becerik-Gerber, B., Jazizadeh, F., Li, N., and Calis, G. (2012). Application Areas and Data Requirements for BIM-Enabled Facilities Management. J. Constr. Eng. Manag.10.1061/(ASCE)CO.1943-7862.0000433 ↗
6. Integrating Building Information Modeling (BIM) and Sensor Technology for Facility Management in 2019
7. Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation10.1016/j.ress.2006.01.006 ↗
8. IFC BIM-based facility management approach to optimize data collection for corrective maintenance10.1061/(ASCE)CF.1943-5509.0000941 ↗
9. A proactive decision making framework for condition-based maintenance10.1108/IMDS-03-2015-0071 ↗
10. Bouabdallaoui, Y., Lafhaj, Z., Yim, P., Ducoulombier, L., and Bennadji, B. (2021). Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach. Sensors, 21.10.3390/s21041044 ↗
11. Aliev, K., and Antonelli, D. (2021). Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning. Appl. Sci., 11.10.3390/app11041621 ↗
12. Anomaly Detection Based on Sensor Data in Petroleum Industry Applications10.3390/s150202774 ↗
13. Dave, B., Buda, A., Nurminen, A., and Främling, K. (2018). A framework for integrating BIM and IoT through open standards. Automation in Construction, Elsevier.10.1016/j.autcon.2018.07.022 ↗
14. Krishnamurthy, S., Anson, O., Sapir, L., Glezer, C., Rois, M., Shub, I., and Schloeder, K. (2008). Automation of facility management processes using machine-to-machine technologies. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4952 LNCS, Springer.10.1007/978-3-540-78731-0_5 ↗
15. Digital technologies in Facility Management–the state of practice and research challenges10.1016/j.proeng.2017.08.059 ↗
16. Cahill, B., Menzel, K., and Flynn, D. (2012). BIM as a Centre Piece for Optimised Building Operation. eWork and eBusiness in Architecture, Engineering and Construction: ECPPM 2014, Taylor & Francis Group.10.1201/b12516-88 ↗
17. Marzouk, M., and Abdelaty, A. (2014). BIM-based framework for managing performance of subway stations. Automation in Construction, Elsevier B.V.10.1016/j.autcon.2014.02.004 ↗
18. Data Driven Indoor Air Quality Prediction in Educational Facilities Based on IoT Network10.1016/j.enbuild.2021.110782 ↗
19. Rinaldi, S., Flammini, A., Tagliabue, L.C., and Ciribini, A. (2019). An IoT Framework for the Assessment of Indoor Conditions and Estimation of Occupancy Rates: Results from a Real Case Study, ACTA IMEKO.10.21014/acta_imeko.v8i2.647 ↗
20. Digitisation in facilities management: A literature review and future research directions10.1016/j.autcon.2018.04.006 ↗
21. Xiao, Y.-Q., Li, S.-W., and Hu, Z.-Z. (2019). Automatically Generating a MEP Logic Chain from Building Information Models with Identification Rules. Appl. Sci., 9.10.3390/app9112204 ↗
22. Mannino, A., Dejaco, M.C., and Re Cecconi, F. (2021). Building Information Modelling and Internet of Things Integration for Facility Management—Literature Review and Future Needs. Appl. Sci., 11.10.3390/app11073062 ↗
23. Development of an IoT and BIM-based automated alert system for thermal comfort monitoring in buildings10.1016/j.scs.2020.102602 ↗
24. Wehbe, R., and Shahrour, I. (2019). Use of BIM and Smart Monitoring for buildings’ Indoor Comfort Control. MATEC Web of Conferences, EDP Science.10.1051/matecconf/201929502010 ↗
25. Natephra, W., and Motamedi, A. (2019). Bim-Based Live Sensor Data Visualization Using Virtual Reality for Monitoring Indoor Conditions, CumInCAD.10.52842/conf.caadria.2019.2.191 ↗
26. BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings10.3390/su13084496 ↗
27. Guillen, A., Crespo, A., Gómez, J., González-Prida, V., Kobbacy, K., and Shariff, S. (2016). Building Information Modeling as Asset Management Tool. 3rd IFAC Workshop on Advanced Maintenance Engineering, Services and Technology AMEST 2016, Elsevier B.V.. IFAC-PapersOnLine.10.1016/j.ifacol.2016.11.033 ↗
28. Analysis of an information monitoring and diagnostic system to improve building operations10.1016/S0378-7788(01)00068-8 ↗
29. Piette, M.A., Nordman, B., and Greenberg, S. (1994). Quantifying energy savings from commissioning: Preliminary results from the pacific northwest. Processings of the Second National Conference on Building Commissioning, Lawrence Berkeley National Laboratory.
30. A rule-based fault detection method for air handling units10.1016/j.enbuild.2006.04.014 ↗
31. Mills, E. (2010). Building commissioning: A golden opportunity for reducing energy costs and greenhouse-gas emissions. Lawrence Berkeley National Laboratory, Springer Nature.10.2172/985240 ↗
32. A Bim-Based Location Aware Ar Collaborative Framework for Facility Maintenance Management
33. Chung, S.W., Kwon, S.W., Moon, D.Y., and Ko, T.K. (2018, January 20–25). Smart facility management systems utilising open BIM and augmented/virtual reality. Proceedings of the 35th International Symposium on Automation and Robotics in Construction (ISARC2018), Berlin, Germany.10.22260/ISARC2018/0118 ↗
34. (2017). International Standard Facility Management—Vocabulary, ISO.
35. Developing of Building Maintenance Management by Using BIM
36. Indoor Air Quality Monitoring Systems and COVID-19
37. Laustsen, J. (2008). Energy efficiency requirements in building codes, energy efficiency policies for new buildings. International Energy Agency (IEA), IEA. IEA Information Paper.
38. DoE, U.S. (2011). Buildings Energy Data Book, Energy Efficiency Renewable Energy Department, IEER.
39. Hyvarinen, J., and Karki, S. (1996). Building Optimisation and Fault Diagnosis Source Book, International Energy Agency. IEA Annex.
40. Haves, P., Claridge, D., and Lui, M. (2001). Report assessing the Limitations of EnergPlus and SEAP with Options for Overcoming Those Limitations, California Energy Commission Public Interest Energy Research Program. HPCBS #E5P2.3T1.
41. (2000). CIBSE Guide H: Building Control Systems, Butterworth-Heinemann.
42. Friedman, H., and Piette, M.A. (2001). Comparative Guide to Emerging Diagnostic Tools for Large Commercial HVAC Systems. Ernest Orlando Lawrence Berkeley National Laboratory, LBNL 48629, Ernest Orlando Lawrence Berkeley National Laboratory, LBNL.10.2172/787155 ↗
43. Glaessgen, E., and Stargel, D. (2012, January 23–26). The Digital Twin Paradigm for Future NASA and US Air Force Vehicles. Proceedings of the 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA, Honolulu, HI, USA.10.2514/6.2012-1818 ↗
44. A cyber-physical system approach for building efficiency monitoring10.1016/j.autcon.2019.02.010 ↗
45. Experimentable digital twins10.1109/TII.2018.2804917 ↗
46. Internet of Things applications: A Systematic Review10.1016/j.comnet.2018.12.008 ↗
47. Internet of Things (IoT): A vision, architectural elements, and future directions10.1016/j.future.2013.01.010 ↗
48. IoT and its connectivity challenges in smart home
49. Investigation Internet of Things (IoT) Device using Integrated Digital Forensics Investigation Framework (IDFIF)10.1088/1742-6596/1179/1/012140 ↗
50. Towards utilising internet of things (IoT) devices for understanding individual occupants’ energy usage of personal and shared appliances in office buildings10.1016/j.jobe.2019.100948 ↗
51. Wang, M., Zhang, G., Zhang, C., Zhang, J., and Li, C. (2013, January 9–11). An IoT-based appliance control system for smart homes. Proceedings of the IEEE 4th International Conference on Intelligent Control and Information Processing (ICICIP), Beijing, China.10.1109/ICICIP.2013.6568171 ↗
52. Shaping the digital twin for design and production engineering10.1016/j.cirp.2017.04.040 ↗
53. A review of the roles of digital twin in cps-based production systems10.1016/j.promfg.2017.07.198 ↗
54. Luo, W., Hu, T., Zhu, W., and Tao, F. (2018). Digital twin modeling method for cnc machine tool. 2018 IEEE 15th Int Conf in Networking; Sensing and Control, IEEE.10.1109/ICNSC.2018.8361285 ↗
55. Grieves, M. (2021, June 06). Digital Twin: Manufacturing Excellence Through Virtual Factory Replication. Available online: https://www.researchgate.net/publication/329311603_digital_twin_manufacturing_excellence_through_virtual_factory_replication.
56. Digital twins: The convergence of multimedia technologies10.1109/MMUL.2018.023121167 ↗
57. Boschert, S., and Rosen, R. (2016). Digital twin_The simulation aspect. Mechatronic Futures, Springer.10.1007/978-3-319-32156-1_5 ↗
58. Hicks, B. (2021, June 06). Industry 4.0 and Digital Twins: Key Lessons from NASA. Available online: https://www.thefuturefactory.com/blog/24.
59. Nasaruddin, A.N., Ito, T., and Tuan, T.B. (2018, January 16–18). Digital twin approach to building information management. Proceedings of the Manufacturing Systems Division Conference, Stockholm, Sweden.10.1299/jsmemsd.2018.304 ↗
60. Digital Twin: Values, Challenges and Enablers from a Modeling Perspective10.1109/ACCESS.2020.2970143 ↗
61. (2021, June 06). Digital Twins for IoT Applications: A Comprehensive Approach to Implementing IoT Digital Twins. Available online: https://pdf4pro.com/view/digital-twins-for-iot-applications-oracle-5b4880.html.
62. Del Giudice, M., and Osello, A. (2021). Digital Twin for Smart School Buildings: State of the Art, Challenges, and Opportunities. Handbook of Research on Developing Smart Cities Based on Digital Twins, IGI Global.10.4018/978-1-7998-7091-3 ↗
63. Daily, J., and Peterson, J. (2017). Predictive maintenance: How big data analysis can improve maintenance. Supply Chain Integration Challenges in Commercial Aerospace, Springer.10.1007/978-3-319-46155-7_18 ↗
64. Market Research Future (2019, January 23). Global Digital Twin Market Is Estimated to Grow at a Cagr of 37% from 2017 to 2023. Available online: https://www.marketresearchfuture.com/reports/digital-twin-market-4504.
65. NIBS (2021, February 20). National BIM Guide for Owners. Available online: https://www.nibs.org/files/pdfs/NIBS_BIMC_NationalBIMGuide.pdf.
66. A hybrid conceptual model for BIM in FM10.1108/CI-05-2018-0043 ↗
67. Tagliabue, L.C., and Villa, V. (2017). Il Bim per le Scuole. Analisi del Patrimonio Scolastico e Strategie Di Intervento, Il BIM per le Scuole.
68. Business value of integrated BIM-based asset management10.1108/ECAM-03-2018-0105 ↗
69. Integration of facility management and building information modeling (BIM)10.1108/F-03-2018-0043 ↗
70. The building information modelling trajectory in facilities management: A review10.1016/j.autcon.2016.12.003 ↗
71. BIM for facilities management: Evaluating BIM standards in asset register creation and service life planning
72. Using BIM capabilities to improve existing building energy modelling practices10.1108/ECAM-11-2015-0181 ↗
73. A 6-Step Systematic Process for Model-Based Facility Data Delivery
74. A conceptual framework for integrating building information modeling with augmented reality10.1016/j.autcon.2012.10.012 ↗
75. Remote interactive collaboration in facilities management using BIM-based mixed reality10.1016/j.autcon.2019.102940 ↗
76. Bim integration in augmented reality model10.14716/ijtech.v10i7.3278 ↗
77. Framework based on building information modeling, mixed reality, and a cloud platform to support information flow in facility management10.1007/s42524-019-0071-y ↗