From sensing to action: A digital framework for bridge management

The continuous digitalization of bridge management is transforming how infrastructures are monitored, assessed, and maintained. Despite the availability of sensor data and AI-driven diagnostics, ensuring reliability, transparency, and traceability across the decision-making process remains challenging. This work presents a vision for an integrated, verifiable, and automated bridge management framework that links sensing, assessment, and intervention through emerging digital technologies. Advances in Artificial Intelligence and Machine Learning enable data-driven Structural Health Monitoring for damage detection and quantification under varying conditions. When combined within a Digital Management Environment (DME) compliant with a Digital Twin (DT) framework, these tools support real-time condition assessment and predictive maintenance through interaction between physical and virtual assets. To ensure trust and accountability, blockchain is introduced as a tamper-proof layer for certifying data provenance and AI-based decisions. Smart contracts can automate maintenance workflows while preserving human oversight in safety-critical operations.