Maintenance and protection of road infrastructures (RIs) are increasingly exposed to natural hazards. This requires an effective risk assessment and mitigation methodologies considering a suitable resilience approach. Accordingly, several research projects focusing on RIs have developed resilience frameworks built on anticipatory, absorptive, restorative, and adaptive capacities. Among these, PANOPTIS conceptual resilience framework deals with scenarios linked to disastrous events based on actual data-driven from sensors (terrestrial and airborne). The main aim of PANOPTIS is minimizing service interruptions and quickly recovering with a holistic approach through an integrated platform with structural and geotechnical simulation tools. This paper presents the use of sensors-based monitoring systems: skid resistance measurements through novel mobile and passive road sensors for road surface; and in-situ measurements by a remote-real-time-automated monitoring of corrosion velocity in steel rebars of reinforced concrete bridge structures. Data collected from sensors are processed using automated algorithms to assess the monitored RI states depending on various alert thresholds of control parameters for each application (e.g., corrosion rate and velocity, ice percentage, road surface friction, etc.). These parameters are integrated in a specific platform provided to support decisions-making owners, in this case RI operators. These RI operational monitoring systems contribute in the assessment of RI resilience, in particular for resilience indicators related to the anticipatory capacity of the system. Monitoring data plays a key role in risk reduction and control strategies against negative impacts of disruptive scenario, and to build resilience improving the continuity of RI service. Besides that, broadened idea of the monitoring on-site data reliability is presented.