The combination of IoT and AI technologies for improving concrete curing processes, has led to significant advancement in the construction industries to improve quality control and characteristic monitoring. Traditional curing techniques rely on predefined routines, ambient parameters, and previously experienced assumptions. They often overlook the complex nature of cement-based hydration in real conditions. Smart curing systems apply embedded IoT sensors and engineered probes to monitor in real-time the key parameters such as temperature, humidity, and chemical nature of the cement matrix at different depths of the concrete element. These sensors and probes transmit real-time analog data to central units and platforms where AI-based algorithms will evaluate the data to report accurate results about the hydration process, mechanical property development, and probable risks such as early-age cracking or poor structure of the material.
Using this continuous stream of data and prediction models made by the software, smart curing technologies can enable the possibility of more logic-based decision-making on-site or in factories. Engineers and project managers would be able to adjust curing strategies in real-time to ensure optimal hydration and reducing the cases of under- or over-cured concrete. Furthermore, AI-driven systems are able to predict concrete performance at later ages based on environmental conditions and historical data. This technology allows concrete experts to plan and mange resources more precisely. This data-driven approach not only may improve the durability and quality of concrete structures but also is in good terms agreeing with modern sustainability targets which means: minimized material waste, reduced mistakes and repetitions, and the last but not the least, optimizing energy consumption during the curing operation.
