Journal of Machine and Computing


IoT Innovations as a Strategy for Minimizing Construction Expenses



Journal of Machine and Computing

Received On : 02 September 2023

Revised On : 15 January 2024

Accepted On : 02 February 2024

Published On : 05 April 2024

Volume 04, Issue 02

Pages : 349-359


Abstract


The revolutionary impact of Internet of Things (IoT) improvements on the construction enterprise is carefully tested on this extensive research, with a focus on cost-cutting strategies. Examining a wide range of IoT programs from the predictive repair of equipment to the actual-time monitoring of building materials the study highlights how those packages can appreciably lessen operating charges. This inquiry identifies key areas wherein IoT technology are expected to sell cost-saving measures by utilizing a thorough evaluation of relevant literature along with a robust method that includes case research and empirical records evaluation. Using 12 records points and a aggregate of documentation evaluation and interviews, this examine assesses the impact of IoT technology on constructing charges. It offers insights into how IoT adoption in creation might be financially viable with the aid of highlighting the way it influences fee dynamics and undertaking control. The observe concludes with the aid of dropping mild at the broader implications of IoT adoption inside the construction enterprise and emphasizing how important it is to promoting a sustainable environment and strengthening the competitive fringe of companies on this zone. The present investigation not only emphasizes the economic blessings of implementing IoT, but additionally indicates its capability to convert conventional building methods by way of facilitating the improvement of greater reasonably priced, efficient, and environmentally friendly venture execution strategies.


Keywords


IoT in Construction, Cost Reduction Strategies, Construction Efficiency, Predictive Maintenance, Real-time Monitoring, Resource Optimization, Sustainable Construction Practices, Construction Project Management


  1. J. M. Ahn, W. Lee, and L. Mortara, “Do government R&D subsidies stimulate collaboration initiatives in private firms?,” Technological Forecasting and Social Change, vol. 151, p. 119840, Feb. 2020, doi: 10.1016/j.techfore.2019.119840.
  2. N. Akhtar, M. A. A. K. Jalwana, M. Bennamoun, and A. Mian, “Attack to Fool and Explain Deep Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 10, pp. 5980–5995, Oct. 2022, doi: 10.1109/tpami.2021.3083769.
  3. A. Arnab, O. Miksik, and P. H. S. Torr, “On the Robustness of Semantic Segmentation Models to Adversarial Attacks,” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun. 2018, doi: 10.1109/cvpr.2018.00099.
  4. R. Chiappini, B. Montmartin, S. Pommet, and S. Demaria, “Can direct innovation subsidies relax SMEs’ financial constraints?,” Research Policy, vol. 51, no. 5, p. 104493, Jun. 2022, doi: 10.1016/j.respol.2022.104493.
  5. D. Czarnitzki and J. Delanote, “R&D policies for young SMEs: input and output effects,” Small Business Economics, vol. 45, no. 3, pp. 465–485, May 2015, doi: 10.1007/s11187-015-9661-1.
  6. A. Díaz, K. Rowshankish, and T. Saleh, “Why data culture matters,” McKinsey Quarterly, 2018(3), 1–17, 2018.
  7. I. Goodfellow, P. McDaniel, and N. Papernot, “Making machine learning robust against adversarial inputs,” Communications of the ACM, vol. 61, no. 7, pp. 56–66, Jun. 2018, doi: 10.1145/3134599.
  8. Q. Li, M. Wang, and L. Xiangli, “Do government subsidies promote new-energy firms’ innovation? Evidence from dynamic and threshold models,” Journal of Cleaner Production, vol. 286, p. 124992, Mar. 2021, doi: 10.1016/j.jclepro.2020.124992.
  9. Y. Liu, “Research on the influence of data analysis ability of employees in aerospace enterprises on individual work performance,” (Ph.D. dissertation). Harbin Institute of Technology, Heilongjiang, China, 2020.
  10. A. Manzoor, M. Liyanage, A. Braeke, S. S. Kanhere, and M. Ylianttila, “Blockchain based Proxy Re-Encryption Scheme for Secure IoT Data Sharing,” 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), May 2019, doi: 10.1109/bloc.2019.8751336.
  11. OECD “Science, Technology and Innovation Outlook 2023: Enabling Transitions in Times of Disruption,” Washington, DC, USA: OECD Publishing, 2023.
  12. J. Pan, J. Wang, A. Hester, I. Alqerm, Y. Liu, and Y. Zhao, “EdgeChain: An Edge-IoT Framework and Prototype Based on Blockchain and Smart Contracts,” IEEE Internet of Things Journal, vol. 6, no. 3, pp. 4719–4732, Jun. 2019, doi: 10.1109/jiot.2018.2878154.
  13. A. Patil, A. Pawar, D. Patil, and A. Kolte, “Assessment of Barriers for Small Scale Contractors in Adopting Sustainable Construction Practices: The Perspective of Indian Construction Industry,” International Journal of Business and Globalisation, vol. 1, no. 1, p. 1, 2021, doi: 10.1504/ijbg.2021.10039856.
  14. D. T. Patil and A. Bhaumik, “Efficiency of Internet of Things (IoT)-Enabled Systems in Reducing Construction Cost,” 2023 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), Mar. 2023, doi: 10.1109/iccike58312.2023.10131697.
  15. M. Shafique et al., “Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead,” IEEE Design & Test, vol. 37, no. 2, pp. 30–57, Apr. 2020, doi: 10.1109/mdat.2020.2971217.
  16. A. Tiwari and U. Batra, “IPFS enabled blockchain for smart cities,” International Journal of Information Technology, vol. 13, no. 1, pp. 201–211, Nov. 2020, doi: 10.1007/s41870-020-00568-9.
  17. W. Xueyan, “Research on the influence mechanism of institution-based trust on information disclosure intention in mobile office application,” (Ph.D. dissertation). Harbin Institute of Technology, Heilongjiang, China, 2020.
  18. J. Zhang and C. Li, “Adversarial Examples: Opportunities and Challenges,” IEEE Transactions on Neural Networks and Learning Systems, pp. 1–16, 2019, doi: 10.1109/tnnls.2019.2933524.
  19. X. Zheng, J. Lu, S. Sun, and D. Kiritsis, “Decentralized Industrial IoT Data Management Based on Blockchain and IPFS,” Advances in Production Management Systems. Towards Smart and Digital Manufacturing, pp. 222–229, 2020, doi: 10.1007/978-3-030-57997-5_26.

Acknowledgements


We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


Funding


No funding was received to assist with the preparation of this manuscript.


Ethics declarations


Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.


Availability of data and materials


Data sharing is not applicable to this article as no new data were created or analysed in this study.


Author information


Contributions

All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.


Corresponding author


Rights and permissions


Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/


Cite this article


Deepak Tulsiram Patil and Amiya Bhaumik, “IoT Innovations as a Strategy for Minimizing Construction Expenses", pp. 349-359, April 2024. doi: 10.53759/7669/jmc202404033.


Copyright


© 2024 Deepak Tulsiram Patil and Amiya Bhaumik. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.