Real-time monitoring and prediction of water content in concrete members through time series modeling

• Monitors moisture in concrete via IoT sensors for 21 days. • Forecasts moisture using Holt-Winters’ method with high accuracy. • Reduces construction time and ensures durable, reliable concrete. • Practical application with embedded sensors and predictive analytics. The quality control of concrete is a significant barometer for ensuring a timely and robust construction program. IoT provides exciting possibilities of ensuring real time data is collected and analyzed to ensure actionable insights and facilitate decision-making in the construction industry. This study sheds some light on exactly how this can be done using wireless sensors embedded in a concrete sample to provide a real-time moisture profile of the concrete sample as it cures and attains strength over a period of 21 days. Time series forecasting using Holt-Winters’ method is then used to forecast the future moisture profile of the concrete sample with a high degree of accuracy. This has significant implications in reducing construction time while also ensuring durable concrete with high reliability. The real-time monitoring and prediction of water content in concrete members through time series modeling provides a valuable tool for construction professionals to ensure the quality and longevity of their buildings. The proposed method can be applied in practice by using embedded sensors to gather data and analyzing it using predictive analytics.