IOT-enabled framework for monitoring carbon emissions in the materialization phase of modular integrated construction
DOI: https://doi.org/10.3846/jcem.2026.25215Abstract
The potential of Modular Integrated Construction (MiC) to reduce carbon emissions (CEs) has led to increased attention on developing rigorous monitoring systems. Existing methods predominantly capture CEs of isolated MiC stages, overlooking nuances of arrangeable and reusable activities, thus hindering effective CE control measures. To overcome this limitation, this study develops an Internet of Things (IoT)-enabled framework for monitoring CEs of MiC, specifically focusing on the materialization phase, integrating across various MiC stages and facilitating detailed monitoring of CEs associated with arrangeable and reusable activities. This study builds up a CE measurement model tailored to the MiC materialization phase, providing a computational basis for a subsequent monitoring framework. By leveraging IoT technology, the framework is evaluated through case studies to confirm its feasibility and efficacy. The results indicate that the framework enabled improved monitoring capabilities, and the CEs of many MiC activities are successfully integrated into the system. The case study analysis demonstrates that the system's feedback-driven adjustments achieved a CE reduction of 732.04 metric tons.
Keywords:
MiC, materialization phase, IoT, monitoring framework, carbon emissionHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Aheleroff, S., Xu, X., Lu, Y., Aristizabal, M., Pablo Velasquez, J., Joa, B., & Valencia, Y. (2020). IoT-enabled smart appliances under industry 4.0: A case study. Advanced Engineering Informatics, 43, Article 101043. https://doi.org/10.1016/j.aei.2020.101043
Al-Kodmany, K. (2023). Smart elevator systems. Journal of Mechanical Materials and Mechanics Research, 6(1), 41–53. https://doi.org/10.30564/jmmmr.v6i1.5503
Alsamhi, S. H., Afghah, F., Sahal, R., Hawbani, A., Al-qaness, M. A., Lee, B., & Guizani, M. (2021). Green internet of things using UAVs in B5G networks: A review of applications and strategies. Ad Hoc Networks, 117, Article 102505. https://doi.org/10.1016/j.adhoc.2021.102505
Asif, M., Abrar, M., Salam, A., Amin, F., Ullah, F., Shah, S., & AlSalman, H. (2025). Intelligent two-phase dual authentication framework for Internet of Medical Things. Scientific Reports, 15(1), Article 1760. https://doi.org/10.1038/s41598-024-84713-5
Avancini, D. B., Rodrigues, J. J., Martins, S. G., Rabêlo, R. A., Al-Muhtadi, J., & Solic, P. (2019). Energy meters evolution in smart grids: A review. Journal of Cleaner Production, 217, 702–715. https://doi.org/10.1016/j.jclepro.2019.01.229
Chen, W., Yang, S., Zhang, X., Jordan, N. D., & Huang, J. (2022). Embodied energy and carbon emissions of building materials in China. Building and Environment, 207, Article 108434. https://doi.org/10.1016/j.buildenv.2021.108434
Dams, B., Maskell, D., Shea, A., Allen, S., Driesser, M., Kretschmann, T., Walker, P., & Emmitt, S. (2021). A circular construction evaluation framework to promote designing for disassembly and adaptability. Journal of Cleaner Production, 316, Article 128122. https://doi.org/10.1016/j.jclepro.2021.128122
Georgakopoulos, D., & Jayaraman, P. P. (2016). Internet of things: From internet scale sensing to smart services. Computing, 98(10), 1041–1058. https://doi.org/10.1007/s00607-016-0510-0
Guerra-Santin, O., & Tweed, C. A. (2015). In-use monitoring of buildings: An overview of data collection methods. Energy and Buildings, 93, 189–207. https://doi.org/10.1016/j.enbuild.2015.02.042
Hackmann, G., Guo, W., Yan, G., Lu, C., & Dyke, S. (2013). Cyber-physical codesign of distributed structural health monitoring with wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 25(1), 63–72. https://doi.org/10.1109/TPDS.2013.30
Hajibabai, L., Aziz, Z., & Peña‐Mora, F. (2011). Visualizing greenhouse gas emissions from construction activities. Construction Innovation, 11(3), 356–370. https://doi.org/10.1108/14714171111149052
Hao, J. L., Cheng, B., Lu, W., Xu, J., Wang, J., Bu, W., & Guo, Z. (2020). Carbon emission reduction in prefabrication construction during materialization stage: A BIM-based life-cycle assessment approach. Science of the Total Environment, 723, Article 137870. https://doi.org/10.1016/j.scitotenv.2020.137870
He, B., & Bai, K.-J. (2020). Digital twin-based sustainable intelligent manufacturing: A review. Advances in Manufacturing, 9(1), 1–21. https://doi.org/10.1007/s40436-020-00302-5
Huang, X., Xu, Y., & Wu, S. (2022). Research on spplication of BIM technology in building carbon emission intelligent monitoring system. In 2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA). IEEE. https://doi.org/10.1109/EEBDA53927.2022.9744904
Jia, M., Komeily, A., Wang, Y., & Srinivasan, R. S. (2019). Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications. Automation in Construction, 101, 111–126. https://doi.org/10.1016/j.autcon.2019.01.023
Johannesen, N. J., Kolhe, M., & Goodwin, M. (2019). Relative evaluation of regression tools for urban area electrical energy demand forecasting. Journal of Cleaner Production, 218, 555–564. https://doi.org/10.1016/j.jclepro.2019.01.108
Kamel, S. O. M., & Hegazi, N. H. (2018). A proposed model of IoT security management system based on a study of internet of things (IoT) security. International Journal of Scientific & Engineering Research, 9(9), 1227–1244.
Kedir, F., & Hall, D. M. (2021). Resource efficiency in industrialized housing construction – A systematic review of current performance and future opportunities. Journal of Cleaner Production, 286, Article 125443. https://doi.org/10.1016/j.jclepro.2020.125443
laili Jabar, I., Ismail, F., & Mustafa, A. A. (2013). Issues in managing construction phase of IBS projects. Procedia - Social and Behavioral Sciences, 101, 81–89. https://doi.org/10.1016/j.sbspro.2013.07.181
Li, X., Yan, F., Zuo, F., Zeng, Q., & Luo, L. (2019). Touch well before use: Intuitive and secure authentication for IoT devices. In MobiCom ‘19: The 25th Annual International Conference on Mobile Computing and Networking (Article 33). https://doi.org/10.1145/3300061.3345434
Li, L., Li, Z., Li, X., Zhang, S., & Luo, X. (2020). A new framework of industrialized construction in China: Towards on-site industrialization. Journal of Cleaner Production, 244, Article 118469. https://doi.org/10.1016/j.jclepro.2019.118469
Li, X., Xie, W., Yang, T., Lin, C., & Jim, C. Y. (2023). Carbon emission evaluation of prefabricated concrete composite plates during the building materialization stage. Building and Environment, 232, Article 110045. https://doi.org/10.1016/j.buildenv.2023.110045
Liu, G., Chen, R., Xu, P., Fu, Y., Mao, C., & Hong, J. (2020). Real-time carbon emission monitoring in prefabricated construction. Automation in Construction, 110, Article 102945. https://doi.org/10.1016/j.autcon.2019.102945
Liu, J., Liu, G., Zhao, H., Zhao, J., Qiu, J., & Dong, Z. Y. (2023). A real-time carbon emission estimation framework for industrial parks with non-intrusive load monitoring. Sustainable Energy Technologies and Assessments, 60, Article 103482. https://doi.org/10.1016/j.seta.2023.103482
Loo, B. P., Li, X., & Wong, R. W. (2023). Environmental comparative case studies on modular integrated construction and cast-in-situ construction methods. Journal of Cleaner Production, 428, Article 139303. https://doi.org/10.1016/j.jclepro.2023.139303
Manavalan, E., & Jayakrishna, K. (2019). A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Computers & Industrial Engineering, 127, 925–953. https://doi.org/10.1016/j.cie.2018.11.030
Miklautsch, P., & Woschank, M. (2022). A framework of measures to mitigate greenhouse gas emissions in freight transport: systematic literature review from a manufacturer’s perspective. Journal of Cleaner Production, 366, Article 132883. https://doi.org/10.1016/j.jclepro.2022.132883
Pakdel, A., Ayatollahi, H., & Sattary, S. (2021). Embodied energy and CO2 emissions of life cycle assessment (LCA) in the traditional and contemporary Iranian construction systems. Journal of Building Engineering, 39, Article 102310. https://doi.org/10.1016/j.jobe.2021.102310
Pan, W., & Zhang, Z. (2023). Benchmarking the sustainability of concrete and steel modular construction for buildings in urban development. Sustainable Cities and Society, 90, Article 104400. https://doi.org/10.1016/j.scs.2023.104400
Perwej, Y., Haq, K., Parwej, F., Mumdouh, M., & Hassan, M. (2019). The internet of things (IoT) and its application domains. International Journal of Computer Applications, 182(49), 36–49. https://doi.org/10.5120/ijca2019918763
Qi, B., Razkenari, M., Costin, A., Kibert, C., & Fu, M. (2021). A systematic review of emerging technologies in industrialized construction. Journal of Building Engineering, 39, Article 102265. https://doi.org/10.1016/j.jobe.2021.102265
Sina. (2022). Jiang Yi: Green and low-carbon transformation in the construction sector (in Chinese). https://finance.sina.com.cn/esg/pa/2022-05-12/doc-imcwipii9460275.shtml
Tang, S., Shelden, D. R., Eastman, C. M., Pishdad-Bozorgi, P., & Gao, X. (2019). A review of building information modeling (BIM) and the internet of things (IoT) devices integration: Present status and future trends. Automation in Construction, 101, 127–139. https://doi.org/10.1016/j.autcon.2019.01.020
Tao, X., Mao, C., Xie, F., Liu, G., & Xu, P. (2018). Greenhouse gas emission monitoring system for manufacturing prefabricated components. Automation in Construction, 93, 361–374. https://doi.org/10.1016/j.autcon.2018.05.015
Tsang, Y. P., Choy, K. L., Wu, C.-H., Ho, G. T., Lam, C. H., & Koo, P. (2018). An Internet of Things (IoT)-based risk monitoring system for managing cold supply chain risks. Industrial Management and Data Systems, 118(7), 1432–1462. https://doi.org/10.1108/IMDS-09-2017-0384
United Nations Environment Programme. (2022). 2022 Global status report for buildings and construction.
Wang, Z., Liu, J., Zhang, Y., Yuan, H., Zhang, R., & Srinivasan, R. S. (2021). Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles. Renewable and Sustainable Energy Reviews, 143, Article 110929. https://doi.org/10.1016/j.rser.2021.110929
Wu, H., Li, L., Liu, Y., & Wu, X. (2022). Vehicle-based secure location clustering for IoT-equipped building and facility management in smart city. Building and Environment, 214, Article 108937. https://doi.org/10.1016/j.buildenv.2022.108937
Xu, J., Zhang, Q., Teng, Y., & Pan, W. (2023). Integrating IoT and BIM for tracking and visualising embodied carbon of prefabricated buildings. Building and Environment, 242, Article 110492. https://doi.org/10.1016/j.buildenv.2023.110492
Zahid, H., Elmansoury, O., & Yaagoubi, R. (2021). Dynamic predicted mean vote: An IoT-BIM integrated approach for indoor thermal comfort optimization. Automation in Construction, 129, Article 103805. https://doi.org/10.1016/j.autcon.2021.103805
Zheng, Z., Zhang, Z., & Pan, W. (2020). Virtual prototyping-and transfer learning-enabled module detection for modular integrated construction. Automation in Construction, 120, Article 103387. https://doi.org/10.1016/j.autcon.2020.103387
Zhong, R. Y., Peng, Y., Xue, F., Fang, J., Zou, W., Luo, H., Ng, S. T., Lu, W., Shen, G. Q., & Huang, G. Q. (2017). Prefabricated construction enabled by the Internet-of-Things. Automation in Construction, 76, 59–70. https://doi.org/10.1016/j.autcon.2017.01.006
Zhou, L., Chong, A. Y., & Ngai, E. W. (2015). Supply chain management in the era of the internet of things. International Journal of Production Economics, 159, 1–3. https://doi.org/10.1016/j.ijpe.2014.11.014
View article in other formats
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License

This work is licensed under a Creative Commons Attribution 4.0 International License.