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

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 developing 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.