A
No Action Required
Minimal surface distress. Routine monitoring and normal maintenance are recommended.
Road Condition Analysis
Map every crack before the road fails.
Dronnix combines high-resolution drone mapping and AI-powered analysis to assess road condition across corridors, municipal streets, and private access roads in one repeatable workflow.
High-resolution RGB capture
AI crack and pothole detection
GIS-ready municipal datasets
100%
Road Coverage
Full surface coverage per flight, not sample-only windshield surveys.
1
Flight Workflow
Capture, analysis, condition scoring, and report outputs in one process.
4
Condition Classes
A to D segment scoring for prioritized maintenance planning.
Condition Score Map
Delivered Output
Every defect is tied to location, severity, and maintenance context.
The Challenge
Road damage spreads faster than budgets can react.
Cracks, edge breakup, rutting, and potholes often start as localized surface defects. When they are missed, moisture enters the pavement structure and small repairs become reconstruction work.
Manual road surveys are slow, inconsistent, and difficult to repeat across a full municipal network. Aerial mapping creates a visual record that can be measured, compared, and revisited.
Maintenance plans are stronger when every defect is mapped, measured, and prioritized.
How It Works
Three steps. One flight. Decision-ready output.
Step 1 - Drone mapping. The drone captures systematic, overlap-optimized RGB imagery across the road corridor to create a complete photographic record.
Step 2 - AI defect detection. Computer vision models identify cracks, potholes, surface breakup, rutting, and edge damage with consistent detection thresholds.
Step 3 - Classification and report. Each segment receives a condition class based on defect density and severity, delivered with maps, inventories, and planning summaries.
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Drag to compare raw imagery and AI output
Road Classification
Every road segment gets a condition score.
Defect type, density, and severity are converted into clear classes so maintenance teams can compare segments and plan work by priority.
B
Preventive Treatment
Minor cracking or early wear. Seal coating or localized treatment can extend service life.
C
Scheduled Repair
Moderate defects. Patching, resurfacing, or targeted repair should be planned.
D
Immediate Action
Severe damage. Urgent repair, reconstruction, or safety review is required.
Example output: classified road network
AI Detection & Planning
Consistent inspection criteria across the network.
The same analysis pipeline is applied to every captured road segment, reducing subjective field notes and giving asset managers repeatable condition data.
1
Step 01 - Capture
RGB
Aerial Mapping
High-resolution imagery captured across the road corridor.
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2
Step 02 - AI
AI
Defect Detection
Cracks, potholes, rutting, and edge damage located automatically.
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3
Step 03 - Score
MAP
Condition Mapping
Segments classified by severity and defect concentration.
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4
Step 04 - Deliver
GIS
Planning Dataset
Reports and GIS files prepared for maintenance planning.
Longitudinal Cracks
Linear failures that indicate lane-edge stress, joint movement, or early structural issues.
Transverse Cracks
Cross-road cracking linked to temperature movement, settlement, or pavement fatigue.
Potholes
Open surface failures mapped by location and severity so crews can dispatch targeted repairs.
Alligator Cracking
Clustered fatigue cracking that signals deeper structural failure and higher repair priority.
Rutting
Wheel-path deformation captured and flagged for resurfacing or structural review.
Edge Breakup
Shoulder and lane-edge degradation documented before it expands into travel lanes.
Deliverables
What you receive.
01
Pavement Condition Map
Geo-referenced orthomosaic with color-coded segment scores and visible defect context.
02
Defect Inventory
GIS-ready defect records with type, severity, GPS location, and measured area or length.
03
Priority Summary
Segment ranking and recommended repair priority for municipal planning and budgeting.
04
Annotated Imagery
Marked-up image evidence that helps crews verify field conditions before dispatch.
Why Aerial
Coverage that manual surveys cannot match.
One flight creates a consistent record across the whole route, with less disruption and cleaner data for long-term asset management.
| Capability | Dronnix Road Analysis | Manual Road Survey |
|---|---|---|
| Surface coverage | Full corridor | Visual sample or driven notes |
| Lane closure required | No routine closure | Often required for close inspection |
| Defect location | GPS-tagged records | Manual references |
| Repeatability | Consistent detection workflow | Varies by crew and conditions |
| Planning output | GIS-ready dataset | Report notes and photos |
| Before/after tracking | Comparable imagery over time | Harder to normalize |
Get Started
Start with your road network.
Send us the route, area, or municipal network you want assessed. We will scope the flight plan and quote the deliverables your team needs.