Smart Aggregate Sensor for Simultaneous Multi-Source Information Monitoring: Design Methods and Experimental Evaluation

ABSTRACT

Real-time sensing of the evolution of multi-source parameters within pavement structures is essential for effective construction, performance evaluation, and maintenance. This study develops a wireless smart aggregate (SA) sensor for real-time multiparameter monitoring within pavement mixtures. A strain transfer model for the sensing layer–encapsulation–medium system was derived, validated via finite element simulations, and applied to optimize the encapsulation design. The SA integrates strain gauges, accelerometers, magnetometers, and thermometers to capture stress, acceleration, rotation, and temperature simultaneously. Laboratory calibration verified that the sensor achieves high measurement accuracy, and gyratory compaction tests in cement-stabilized macadam demonstrated the sensor’s capability to track compaction-induced mechanical and kinematic changes. To mitigate material heterogeneity effects, a volatility index (Vt) combining stress and rotation variations was introduced, showing a strong correlation with compaction evolution (Pearson correlation coefficient ≥ 0.89). The results confirm the SA’s potential for multi-source in situ monitoring, offering an effective tool for pavement health assessment and intelligent construction control.