This paper investigates the role of digitalization in transforming structural engineering through predictive monitoring technologies. It presents an innovative Internet of Things (IoT) system integrating smart bolts equipped with ultrasonic and inertial sensors to continuously measure clamping force, vibration response, and inclination in steel joints. Data gathered from distributed sensors are transmitted via advanced communication protocols to a cloud platform, where Machine Learning algorithms perform anomaly detection and trend forecasting. This process enables early identification of structural changes and supports predictive maintenance strategies. The system was validated through two experimental applications. The first concerns the development of the FREEDAM technology at the University of Salerno, where resilient bolted joints for seismic applications were monitored to assess their energy dissipation capacity and self-centering performance. The second involves the structural health monitoring of a large industrial warehouse roof, where real-time analysis revealed stress redistribution during testing and commissioning phases. The results demonstrate that the integration of IoT sensing, artificial intelligence, and data-driven predictive analytics can significantly improve safety, operational efficiency, and sustainability in the lifecycle management of steel and composite structures. The study highlights the potential of digital and intelligent monitoring systems to support a shift from traditional inspection methods to continuous, adaptive, and proactive management of structural performance.