J-FLOW Ecosystems

Check-Up Carretero Intelligent Pavement Evaluation Ecosystem

Check-Up Carretero is an integrated ecosystem for road assessment that combines on edge computer vision, sensor data, and financial analytics to deliver a complete understanding of pavement performance. Using proprietary AI models, it detects and classifies up to 18 types of pavement distresses with high precision, supported by in-situ measurements of rut depth, macrotexture, and IRI.

The system also generates interactive BI dashboards that visualize deterioration patterns, maintenance forecasts, and cost scenarios, enabling faster and smarter decision-making. Each project is developed as a tailor-made solution, fully adaptable to the customer’s operational and financial needs.

Road Signage Inspection and Condition Assessment

This service performs automated detection, classification, and condition evaluation of both horizontal and vertical road signage using AI-based image recognition and georeferenced mapping. It identifies line markings, arrows, symbols, and traffic signs, analyzing their visibility, reflectivity, and physical condition.

The collected data is integrated into BI dashboards that display inventory counts, deterioration levels, and compliance with road safety standards. This enables authorities to plan maintenance actions, optimize replacement programs, and ensure that all signage contributes effectively to safe and efficient mobility.

Predictive Modeling for Pavement Deterioration

Predictive Modeling applies statistical and machine-learning techniques to forecast pavement behavior based on historical data, traffic load, and environmental variables. It predicts deterioration trends and remaining service life to anticipate when and where maintenance will be needed.

This approach enables proactive planning, optimizing intervention timing, and reducing total maintenance costs over the road’s lifespan.

Digital Twins for Infrastructure Simulation

Digital Twins recreate real road networks in virtual environments, synchronizing AI-based inspection data, traffic conditions, and maintenance records. These dynamic simulations allow stakeholders to test infrastructure scenarios, evaluate operational impacts, and visualize deterioration in real time.

Developed using simulation and modeling tools such as PTV Vissim, they enhance decision-making by merging engineering precision with visual clarity.

Dashboards & BI for Data-Driven Decisions

The BI environment centralizes all technical, financial, and predictive information in an interactive interface. Dashboards display key indicators such as IRI trends, distress density, cost projections, and maintenance prioritization across segments.

Designed for technical and executive audiences, these visual tools transform complex datasets into clear, actionable insights that guide planning and investment decisions.

ACB Cost-Benefit Analysis

ACB evaluates the economic and social return of maintenance and rehabilitation strategies through cost-benefit ratios, NPV, and IRR indicators. It compares intervention alternatives to determine the most efficient and impactful solutions.

This analysis ensures that infrastructure investments generate measurable value in safety, mobility, and long-term performance.