Identify pavement defects in real-time, Reduce operational monitoring costs by 80%, Optimise maintenance budget allocation by up to 40%.
A fully automated pipeline — no road closure, no manual computation, no delay. Results in hours, not weeks.
Portable AiOT sensor on a vehicle. No road closure or lane restriction required.
Interactive mapping with condition analytics, risk assessments, heat maps, and performance trends across your entire road asset.
Actual analysis, evaluate deterioration models, and apply AI-assisted regression to forecast future asset conditions.
Build and compare BAU with optimised scenarios across multiple maintenance objectives simultaneously.
Tailored executive report summaries. Seamless sharing of scenarios, templates, and results across teams.
A fully integrated pipeline — each module purpose-built and connected, from field sensor to decision-ready output.
Surveys roads with accurate and precise multi-sensor capture — imagery, GPS, and lane geometry. No road closure required.
Classifies potholes, cracks, raveling, alligator cracking, spalling and more on AC and PCC surfaces, with GPS coordinates and mm dimensions per detection.
GIS maps overlay distress severity on live road networks. Heat maps, colour-coded condition bands, and GPS-linked defect markers.
Automated road performance computation based on international (e.g. ASTM) and local standards — deduct value analysis, CDV, strip charts, and condition-band breakdowns.
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ML models forecast pavement deterioration based on mechanistic empirical methods, enabling proactive maintenance planning before condition failure.
Shifts authorities from reactive repair to preventive management, significantly reducing total lifecycle cost.
A virtual replica of the road network, synchronised with real survey data, simulating maintenance interventions.
Every process enhanced by AI, produces a complete set of smart and optimized analytical reports.
Road Performance Index based on International (ASTM) and/or Local Standard
Colour-coded segments per lane completed with accurate location and statistics.
Unlike old method, ATLAS.Pave is designed for speed, accuracy, and actionable intelligence, and most importantly your data is safe and secured.
Singapore-based, developed under rigorous research standards with transparent, auditable AI methodology and peer-reviewed techniques.
PCI, Strip Map, Deduct Value, and Comparative Analysis PDF reports generated instantly — branded and ready to present to stakeholders.
Deep-learning vision with >80% classification accuracy across 7+ pavement distress types on both AC and PCC surfaces.
PCI computation fully complies with ASTM D6433-07 — accepted by road authorities and compatible with existing management frameworks worldwide.
Survey at up to 50 km/h with no road closure. Full network analysis completed within hours — not days or weeks of traditional inspection.
Peer-reviewed methodology grounded in pavement engineering science. Sample-unit analysis with statistical validation ensures defensible results.
Geospatial distress heatmaps overlaid on GIS road networks instantly highlight high-risk corridors across your entire network.
A complete closed-loop system integrating evaluation, prediction, and budgeting into one intelligent decision-support platform.
A direct comparison of AI-powered automated surveying against conventional manual road inspection methods.
| Capability | Traditional Manual Inspection | ATLAS.Pave |
|---|---|---|
| Survey Speed | Walking pace · 1–3 km/day | Up to 50 km/h continuous |
| Road Closure Required | Often required | No — traffic flows normally |
| Data Collection | Manual, paper or tablet | ✓ Fully automated, sensor-fused |
| Data Storage | Manual, risk of information leaking | ✓ Automatic, safe and secure |
| Defect Detection | Human visual judgement | ✓ AI with >80% accuracy |
| Defect Dimensions (mm) | Estimated or absent | ✓ Width, length, depth per defect |
| Location of Defect | Unidentified | ✓ Georeferenced |
| PCI Analysis | Manual · error-prone | ✓ Automated · ASTM Standard |
| GIS / Heat Map | ✗ Not available | ✓ Interactive distress heat maps |
| Predictive Modelling | ✗ Not available | ✓ ML deterioration forecasting |
| Report Generation | Days to weeks | Instant · auto-generated PDF |
| Scalability | Limited by workforce | ✓ Scales to full network |
