Long-term Structural Health Monitoring (SHM) of bridges offers significant advantages over temporary or intermittent monitoring strategies. While short-term or periodic assessments provide limited snapshots of a structure performance, they often fail to capture the full spectrum of environmental and operational influences. This can result in the misinterpretation of standard structural behaviors as anomalies due to incomplete characterization across the various phases and conditions faced during regular operation. In contrast, a continuous, long-term monitoring approach enables the detection of light changes and trends over time, providing a more comprehensive understanding of the bridge behavior. This paper aims to represent the diverse understanding of structural behavior when the monitoring period is less than a complete seasonal cycle, by analyzing the history of data recorded for six different real bridge monitoring applications. These case studies highlight the benefits of long-term SHM for bridges, based on permanent smart sensing systems. These examples, with more than two years of monitoring data per each, demonstrate how the long-term monitoring approach can support both anomaly and damage identification, benefiting from a FE model-based analysis to promptly and accurately identify anomalies and to trace them back to their root causes. The integration of continuous data collection with advanced modelling techniques raises the level of knowledge and facilitates the precise characterization of potential issues, ensuring the long-term safety and reliability of bridge structures as well as supporting proactive and predictive maintenance activities.