SSN INFOTECH SOLUTIONS - SSN INFOTECH SOLUTIONS – Redefining Pavement Mapping with AI & QGIS

SSN INFOTECH SOLUTIONS – Redefining Pavement Mapping with AI & QGIS

SSN Infotech Solutions specializes in revolutionizing pavement inspection and road asset mapping through cutting-edge AI technology and advanced GIS workflows. Our state-of-the-art platform integrates AI-powered distress detection with QGIS-based spatial analysis to deliver highly accurate, GIS-ready outputs for Pavement Condition Index (PCI) assessments.

By leveraging high-resolution geotagged imagery from mobile mapping vehicles, drones, and 360° panoramic cameras, we automatically detect and classify pavement distresses including:

Alligator cracking
Longitudinal and transverse cracking
Block cracking
Edge cracking
Raveling
Rutting
Potholes
Bleeding
Oxidation
Patch deterioration
Bridge joint conditions
Rumble strips
Pavement markings and guardrails

Each distress is spatially tagged, severity-rated (low, medium, high), and fed into our PCI computation pipeline that follows the ASTM D6433 standard for asphalt and concrete pavement evaluation.

With powerful integration into QGIS, our mapping tools provide:

Real-time visualization of pavement distress locations
Segment-based PCI scoring and heatmaps
Attribute-rich shapefile outputs
Exportable reports and dashboards for planners and engineers

We recently completed a 50,000-mile PCI data collection project in the United States, delivering complete PCI analysis for vast road networks—including pavement condition ratings, asset inventories, and geospatial outputs designed for immediate use by DOTs and contractors.

At SSN Infotech Solutions, we are committed to delivering scalable, high-accuracy, and user-friendly solutions that empower governments, consultants, and infrastructure agencies to make data-driven decisions for road maintenance and planning.

Explore the future of pavement assessment with SSN Infotech Solutions—where AI meets GIS to drive smarter infrastructure.

Road assets are critical components of transportation infrastructure that ensure safe and efficient road usage. They include physical features like curb ramps, crosswalks, stop bars, yield signs, and bike lanes, as shown in your image. These assets support traffic regulation, pedestrian accessibility, and multimodal transportation. Proper identification and tagging of these features enable accurate asset management and maintenance planning. Mapping road assets using GIS and satellite imagery enhances infrastructure monitoring and supports data-driven decision-making.

Sidewalk:

Sidewalks are designated pedestrian pathways typically constructed alongside roads to provide safe walking space away from vehicular traffic.
In your image, sidewalks are marked in red labels and run parallel to the road, usually separated by a curb.
They are essential for pedestrian safety, accessibility, and urban walkability.
Sidewalks often intersect with features like curb ramps and crosswalks at intersections.

Pavement Stripes (Road Markings):

These include single solid, double solid, and yellow centerlines, as seen in the image.
Single Solid Lines (purple): Indicate no crossing or lane change is allowed (used for lane discipline).
Double Solid Lines (blue): Strong restriction, often separating opposing directions of traffic.
Centerlines (yellow): Separate traffic moving in opposite directions and help in alignment.
Pavement markings guide both drivers and pedestrians, improve road safety, and regulate traffic flow.
Both elements—sidewalks and pavement stripes—are crucial for a safe, structured, and accessible transportation environment.

Road Polygon – Brief Overview

Definition: Road polygons represent the actual surface area of roadways on a map, capturing their width and length spatially.
Purpose: These polygons are used for calculating road area, width, and pavement inventory, which is essential for maintenance, budgeting, and project planning.
Data Captured:
Road width (measured across the polygon)
Road length
Surface material type (e.g., Asphalt, Concrete)
Condition rating (e.g., Good, Poor) for PCI analysis

Estimating resurfacing costs
Pavement condition assessment (PCI scoring)
Planning drainage, snow removal, and road reconstruction
Visualization: In your image, roads are polygonal bands with colored lines (centerlines, edges) used to represent real-world road dimensions, making it more accurate than simple centerlines.

Road Distress Tagging – Overview

Definition: Road distress tagging is the process of identifying, labeling, and mapping visible pavement damages such as cracks, potholes, raveling, rutting, etc., on geospatial imagery.
Purpose: It helps in evaluating pavement condition, planning maintenance, and computing PCI (Pavement Condition Index) as per standards like ASTM D6433.
Types of Distresses Tagged (as visible in the image):
Longitudinal & Transverse Cracks
Alligator Cracking
Patching
Raveling or Rutting
These are likely represented by colored line segments on top of the road surface.

Benefits:

Enables automated or manual condition surveys
Helps determine severity levels (Low, Medium, High)
Supports budget forecasting and asset prioritization

Visualization:
colored dashed lines represent different types of distress.
Each segment is georeferenced, allowing integration with PCI calculations and GIS maps.