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IoT system implementation for real-time concrete strength prediction: experimental design, variance evaluation, cost analysis, and implementation ease

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Abstract

Concrete is one of the most widely used building materials due to its durability and cost-effectiveness. Accurate prediction of its compressive strength during early stages is crucial for construction project management, particularly for decisions related to formwork removal and scheduling subsequent activities. Traditional methods for strength assessment, such as concrete cube testing, are labor-intensive and may not represent in-situ conditions accurately. This study introduces an innovative, cost-effective IoT-based system using the maturity method to predict concrete compressive strength in real-time. The proposed system leverages easily accessible hardware and open-source software to provide real-time data on concrete strength development, enhancing monitoring accuracy and operational efficiency. We employed the Nurse-Saul maturity equation and developed a comprehensive calibration process to establish a reliable maturity-strength relationship. The system’s implementation was tested on an actual construction site, focusing on optimizing sensor layout and ensuring continuous data transmission. Results demonstrated high accuracy of strength predictions, with percentage errors within acceptable limits as per ASTM standards. Challenges such as Wi-Fi connectivity, power management, and basic data security were addressed during the deployment phase. The study highlights significant cost savings and improved monitoring capabilities compared to traditional methods, providing a practical solution for construction project managers. Future research will focus on scaling the system for larger projects, integrating advanced analytics, enhancing data security, and develo** wireless sensor setups to reduce labor further and improve efficiency. This research underscores the transformative potential of low-cost IoT systems in the construction industry, offering practical solutions for real-time concrete strength monitoring.

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References

  1. Rudeli N, Santilli A, Arrambide F (2015) Striking of vertical concrete elements: an analysis using the maturity method. Eng Struct 95:40–48

    Article  Google Scholar 

  2. Taheri S (2019) A review on five key sensors for monitoring of concrete structures. Constr Build Mater 204:492–509

    Article  Google Scholar 

  3. Kuryłowicz-Cudowska A, Wilde K, Chroscielewski J (2020) Prediction of cast-in-place concrete strength of the extradosed bridge deck based on temperature monitoring and numerical simulations. Constr Build Mater 254:119224

    Article  Google Scholar 

  4. Lachemi M, Hossain K, Anagnostopoulos C (2007) Application of maturity method to slipforming operations: performance validation. Cem Concr Composites 29(4):290–299

    Article  CAS  Google Scholar 

  5. Gasch I, Alvarado Y, Calderón PA (2012) Temperature effects on load transmission between slabs and shores. Eng Struct 39:89–102. https://doi.org/10.1016/j.engstruct.2012.02.004

    Article  Google Scholar 

  6. Calderón P, Alvarado Y, Adam JM (2011) A new simplified procedure to estimate loads on slabs and shoring during the construction of multistorey buildings. Engin Struct 33:1565–1575

    Article  Google Scholar 

  7. Teixeira S, Santilli A, Puente I (2017) Demoulding vertical elements: recommendations for apply maturity functions. Constr Build Mater 145:392–401

    Article  Google Scholar 

  8. Santilli A, Teixeira S, Puente I (2015) Influence of temperature and concrete reinforcement on vertical formwork design. Constr Build Mater 88:188–195

    Article  Google Scholar 

  9. Miller D, Ho NM, Talebian N, Javanbakht Z (2023) Real-time monitoring of early-age compressive strength of concrete using an IoT-enabled monitoring system: an investigative study. Innov Infrastr Solut. https://doi.org/10.1007/S41062-023-01043-7

    Article  Google Scholar 

  10. Kampli G, Chickerur S, Chitawadagi MV (2023) Real-time in-situ strength monitoring of concrete using maturity method of strength prediction via IoT. Mater Today Proc 88:110–118. https://doi.org/10.1016/j.matpr.2023.05.610

    Article  Google Scholar 

  11. De Carufel S, Fahim A, Ghods P, Alizadeh A (2018) Concrete maturity-from theory to application. Giatec, Ottawa

    Google Scholar 

  12. Vázquez-Herrero C, Martínez-Lage I, Sánchez-Tembleque F (2012) A new procedure to ensure structural safety based on the maturity method and limit state theory. Constr Build Mater 35:393–398. https://doi.org/10.1016/j.conbuildmat.2012.04.040

    Article  Google Scholar 

  13. Wang L, Zhou H, Zhang J, Wang Z, Zhang L, Nehdi ML (2023) Prediction of concrete strength considering thermal damage using a modified strength-maturity model. Constr Build Mater. https://doi.org/10.1016/j.conbuildmat.2023.132779

    Article  Google Scholar 

  14. Carino NJ, Leyendecker EV, Fattal SG (1983) Review of the skyline plaza collapse. Concr Int 5:35–42

    Google Scholar 

  15. Lew HS (1980) West-Virginia cooling-tower collapse caused by inadequate concrete strength. Civ Eng 50:62–67

    Google Scholar 

  16. Reddy NM (2023) A study on real time strength assessment of concrete by maturity method. IOP Conf Ser Earth Environ Sci 1130:012017. https://doi.org/10.1088/1755-1315/1130/1/012017

    Article  Google Scholar 

  17. John ST, Roy BK, Sarkar P, Davis R (2019) IoT enabled real-time monitoring system for early-age compressive strength of concrete. J Constr Eng Manag 146:05019020. https://doi.org/10.1061/(asce)co.1943-7862.0001754

    Article  Google Scholar 

  18. Sofi M, Mendis PA, Baweja D (2012) Estimating early-age in situ strength development of concrete slabs. Constr Build Mater 29:659–666. https://doi.org/10.1016/j.conbuildmat.2011.10.019

    Article  Google Scholar 

  19. Saul AGA (1951) Principles underlying the steam curing of concrete at atmospheric pressure. Mag Concr Res 2:127–140. https://doi.org/10.1680/macr.1951.2.6.127

    Article  Google Scholar 

  20. Soutsos M, Kanavaris F (2023) Applicability of the Modified Nurse-Saul (MNS) maturity function for estimating the effect of temperature on the compressive strength of GGBS concretes. Constr Build Mater 381:131250. https://doi.org/10.1016/j.conbuildmat.2023.131250

    Article  Google Scholar 

  21. Nurse RW (1949) Steam curing of concrete. Mag Concr Res 1(2):79–88. https://doi.org/10.1680/Macr.1949.1.2.79

    Article  Google Scholar 

  22. Plowman JM (2015) Maturity and the strength of concrete. Mag Concr Res 8:13–22. https://doi.org/10.1680/Macr.1956.8.22.13

    Article  Google Scholar 

  23. Plowman JM (1956) Maturity and the strength of concrete. Mag Concr Res 8(24):169–183

    Article  Google Scholar 

  24. ASTM S (2004) Standard practice for estimating concrete strength by the maturity method. ASTM C 1074:1074–1093

    Google Scholar 

  25. C918/C918M Standard Test Method for Measuring Early-Age Compressive Strength and Projecting Later-Age Strength.

  26. NEN 5970:2001 Determination of strength of fresh concrete with the method of weighted maturity.

  27. Carino NJ (1984) The maturity method: theory and application. Cem Concr Aggreg 6(2):61–73. https://doi.org/10.1061/40558(2001)17

    Article  Google Scholar 

  28. V.M. Malhotra, N.J. Carino, (2020) The Maturity Method. Handbook on Nondestructive Testing of Concrete. 106–153. https://doi.org/10.1201/9781420040050-10/maturity-method-malhotra-nicholas-carino

  29. Miller D, Ho NM, Talebian N (2022) Monitoring of in-place strength in concrete structures using maturity method: an overview. Structures 44:1081–1104. https://doi.org/10.1016/J.ISTRUC.2022.08.077

    Article  Google Scholar 

  30. Rasmussen RO, Cable JK, Turner DJ, Voigt GF (2004) Strength prediction by using maturity for portland cement concrete pavement construction at airfields. Trans Res Rec. https://doi.org/10.3141/1893-03

    Article  Google Scholar 

  31. Lee CH, Hover KC (2016) Compatible datum temperature and activation energy for concrete maturity. ACI Mater J 113:197–206

    Google Scholar 

  32. John ST, Sarkar P, Davis R (2022) A long-range wide-area network system for monitoring early-age concrete compressive strength. J Constr Eng Manag 149:04022148. https://doi.org/10.1061/(asce)co.1943-7862.0002425

    Article  Google Scholar 

  33. John ST, Philip MS, Singhal A, Sarkar P, Davis R (2021) Development of real-time monitoring system for early age cementitious materials, lecture notes in civil engineering. LNCE 143:461–469. https://doi.org/10.1007/978-981-33-6969-6_40/cover

    Article  Google Scholar 

  34. A. Yikici, I. Bekmezci, E. Surucu, (2021) Wireless Real-Time Monitoring System for Steam Cured Concrete Maturity Calculation. Proceedings-2021 Innovations in Intelligent Systems and Applications Conference, ASYU 2021. https://doi.org/10.1109/ASYU52992.2021.9598989.

  35. A.O. Olaniyi, T. Watanabe, K. Umeda, C. Hashimoto, (2021) IoT-Web-Based Integrated Wireless Sensory Framework for Non-destructive Monitoring and Evaluation of On-Site Concrete Conditions. Lecture Notes in Mechanical Engineering. 527–536. https://doi.org/10.1007/978-981-15-9199-0_50.

  36. J.S. Lim, H. Cruz, M. Pourhomayoun, M. Mazari, (2018) Application of IoT for concrete structural health monitoring, Proceedings-2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018. 1479–1482. https://doi.org/10.1109/CSCI46756.2018.00295.

  37. Waqar A, Khan MB, Shafiq N, Skrzypkowski K, Zagórski K, Zagórska A (2023) Assessment of challenges to the adoption of IOT for the safety management of small construction projects in Malaysia: structural equation modeling approach. Appl Sci. https://doi.org/10.3390/app13053340

    Article  Google Scholar 

  38. Soutsos M, Hatzitheodorou A, Kwasny J, Kanavaris F (2016) Effect of in situ temperature on the early age strength development of concretes with supplementary cementitious materials. Constr Build Mater 103:105–116. https://doi.org/10.1016/j.conbuildmat.2015.11.034

    Article  CAS  Google Scholar 

  39. C1074 Standard Practice for Estimating Concrete Strength by the Maturity Method. ASTM Standards

  40. Bureau of Indian Standards, IS 456 (2000): Plain and Reinforced Concrete-Code of Practice.

  41. Huang Y, **e T, Li C, Yin X (2019) Optimization analysis of the position of thermometers buried in concrete pouring block embedded with cooling pipes. Math Probl Eng. https://doi.org/10.1155/2019/5256839

    Article  Google Scholar 

  42. Peng H, Lin P, **ang Y, Chen WQ, Zhou S, Yang N, Qiao Y (2020) A positioning method of temperature sensors for monitoring dam global thermal field. Front Mater 7:587738. https://doi.org/10.3389/FMATS.2020.587738/BIBTEX

    Article  Google Scholar 

  43. Sargam Y, Faytarouni M, Riding K, Wang K, Jahren C, Shen J (2019) Predicting thermal performance of a mass concrete foundation: a field monitoring case study. Case Stud Constr Mater 11:e00289. https://doi.org/10.1016/j.cscm.2019.e00289

    Article  Google Scholar 

  44. Stoker P, Tian G, Kim JY (2020) Analysis of variance (ANOVA). Basic Quanti Res Method Urban Plan. https://doi.org/10.4324/9780429325021-11/analysis-variance-anova-philip-stoker-guang-tian-ja-young-kim

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Civil Engineering, KLE Technological University, Vidyanagar, Hubballi, Karnataka, 580031, India

    Gurunath Kampli & Manjoykumar Chitawadagi

  2. School of Computer Science & Engineering, KLE Technological University, Vidyanagar, Hubballi, Karnataka, 580031, India

    Satyadhyan Chickerur

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  1. Gurunath Kampli
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Correspondence to Gurunath Kampli.

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Kampli, G., Chickerur, S. & Chitawadagi, M. IoT system implementation for real-time concrete strength prediction: experimental design, variance evaluation, cost analysis, and implementation ease. Innov. Infrastruct. Solut. 9, 260 (2024). https://doi.org/10.1007/s41062-024-01586-3

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