Global transportation networks are facing rising demands and aging infrastructure, making efficient management paramount. For infrastructure operators, relying on traditional, reactive methods is no longer sufficient for long-term planning or sustainability. The solution lies in the strategic application of data analytics, which drives a critical shift from simply responding to failures to adopting proactive and predictive models. Openvia, as the innovation and technology partner of Globalvia, is central to this vision, focusing on developing new services and using integrated data to transform how road assets are monitored and managed.
Our path towards the predictive maintenance
Efficient road maintenance management is essential for ensuring safety, optimizing public resources, and extending infrastructure lifespan. Traditional maintenance, which is categorized as preventive and corrective, is often reactive and can result in costly delays and disruptions. In contrast, predictive road maintenance utilizes advanced tools to anticipate infrastructure failures before they manifest, thereby redefining the entire maintenance management process.
Usually, maintenance actions are scheduled based on performance indicators, historical data, and current infrastructure condition assessments. Solutions like Geomic, a dynamic platform for managing digitized preventive and corrective maintenance of roadways, help streamline these procedures. The objective is to keep roads in better condition for longer periods, minimizing negative impacts on commuters and logistics providers. Through process digitalization, road management becomes more agile and responsive, with every intervention supported by data and linked to measurable Key Performance Indicators (KPIs).
From an infrastructure operator’s standpoint, this is the first and most significant change management process that enables the future digitalization of data-driven decision-making operations.
Openvia has gained crucial experience through several deployments of Geomic, both within and outside the Globalvia Group, helping road operators achieve the first level of digitalization.
The role of cloud services in digitalization
The immense data volume generated by modern smart mobility systems requires robust, scalable, and secure infrastructure. Cloud computing services provide the essential backbone for advanced transportation technology.
Cloud-based platforms offer several key advantages for infrastructure operators:
- Scalability and resilience: cloud solutions provide the flexibility to instantly scale computing power and storage to manage temporary surges in demand, such as during peak travel times. They also include automated backups and failover protocols, ensuring mobility platforms remain operational despite system failures or cyberattacks.
- Integration: moving functions to an On Cloud platform facilitates the integration of multiple mobility solutions within a single ecosystem. This allows centralized control dashboards to aggregate data from public transit, shared mobility, and traffic management systems.
- Collaboration and traceability: cloud platforms support process digitalization by providing centralized access to real-time road data. This fosters collaboration among field teams, supervisors, and decision-makers, standardizing maintenance workflows. This process ensures every intervention is logged and evaluated, enhancing transparency and traceability for stakeholders.
- Digital Twin capabilities: cloud-based systems support digital twin capabilities. This allows operators to replicate physical infrastructure virtually, simulating the impact of various interventions on road health and cost-efficiency without causing physical disruption.
To maintain public trust, choosing cloud providers with proven compliance certifications and implementing strong cybersecurity measures, such as encryption and strict access controls, is vital.
In this sense, Openvia and Globalvia are at the forefront of cloud transformation, currently migrating all existing Geomic systems to a cloud-based solution, which is already deployed in the first client. We firmly believe this is an essential backbone for boosting operational digital transformation and creating additional operating value.
Harnessing AI and automated inspections for deeper diagnostics
Smarter decision-making in mobility is founded on the capability to collect, process, and analyze massive volumes of data. This vast dataset originates from diverse sources, including vehicle telemetry, weather sensors, structural health monitoring systems, and maintenance records. Consolidating these inputs into integrated platforms provides operators with a holistic view of infrastructure health.
Artificial Intelligence (AI) algorithms are vital because they analyze patterns within this data to achieve deeper diagnostics. AI helps detect early signs of road deterioration, such as cracks, surface wear, potholes, and drainage issues, often identifying defects invisible during manual inspections.
Automated inspection technologies, including drones, mobile units, and sensor-equipped vehicles, collect high-resolution images and structural data without interrupting traffic. These inspections feed directly into the AI engine, providing faster and more precise diagnostics. This allows infrastructure operators to schedule maintenance based on the actual performance of the road rather than on general, often inefficient, estimations.
Nevertheless, AI by itself doesn’t enable additional value without proper integration with asset management systems. Therefore, Geomic allows for different approaches in this integration, depending on the state-of-the-art in terms of architecture, data, and clients’ needs, to deliver the expected AI value.
Operational improvements and sustainability outcomes
Driven by operational digitalization, cloud capabilities, and integration with AI, the transition to data-driven decision-making will be seamless, leading to significant improvements in infrastructure performance, efficiency, and sustainability.
- Operational and economic benefits: by identifying minor issues before they escalate, predictive systems reduce the need for emergency repairs, resulting in fewer emergency repairs, reduced downtime, and better use of maintenance budgets. Early interventions are less expensive in terms of labor and materials. This proactive approach also prevents accelerated degradation, extending the overall durability and lifespan of assets like roads, guardrails, and lighting. Predictive insights enable managers to shift from reactive crisis management to long-term strategic planning, optimizing resource allocation.
- Enhanced sustainability and environmentally responsible maintenance practices. Optimized routes and schedules reduce fuel consumption for maintenance fleets, contributing to lower emissions. Extending the lifespan of pavements and assets also means fewer materials are consumed over time. This alignment supports the broader goals of sustainable urban mobility, aiming for cleaner and more energy-efficient transportation systems.
Building the future of asset management
Data analytics is a dynamic framework designed to evolve with the needs of enhanced asset management. Openvia empowers infrastructure managers to utilize data, collaboration, and advanced technology to build smarter, safer, and more sustainable mobility networks. Embracing AI and data analytics is a strategic imperative for road networks designed for the complexities of the next decade.
