The Assignment
Road infrastructure authorities require reliable and up-to-date information about both roadway condition and the assets distributed along the network to plan maintenance, rehabilitation and infrastructure investments effectively.
CS TECH Ai supported road asset management through systematic field data acquisition and geospatial mapping. The objective was to create a structured inventory of road assets and capture condition-related information that could support assessment of maintenance requirements and better infrastructure decision-making.
Our Approach
CS TECH Ai combined mobile LiDAR, GPS-enabled spatial data capture and field-based visual assessment to document road infrastructure and its operating condition.
The engagement included:
- Mobile LiDAR-based roadway and roadside data acquisition
- GPS-enabled location capture
- Visual inspection of road infrastructure
- Creation of road and asset inventories
- Collection of asset-condition information
- GIS mapping of streets and road infrastructure
- Updating of existing road-asset databases
- Use of LiDAR imagery to support assessment of maintenance requirements
- Processing and organization of captured information for subsequent asset-management workflows
This created a geospatially referenced information base connecting the physical location of infrastructure assets with information about their condition and maintenance requirements.
Road & Asset Intelligence
The road asset management framework supports multiple areas of infrastructure assessment, including:
- Road and asset inventory
- Pavement condition
- Pavement riding quality
- Subgrade assessment
- Pavement strength evaluation
- Traffic estimation
- Bridge condition assessment
For road and asset inventory specifically, the captured information can be used to establish a database of road assets and their operating condition, analyse maintenance requirements using LiDAR imagery and update GIS-based street information. Transportation Deck_V2 (1)
From Field Capture to Asset Information
The data-acquisition workflow provides a structured path from the physical road network to information that can support infrastructure management:
Road & Roadside Infrastructure → GPS / LiDAR / Visual Data Capture → Processing & Asset Identification → GIS Mapping & Asset Inventory → Condition Assessment → Maintenance Planning
CS TECH Ai's broader roadside GIS workflow also supports processing registered scan data, manual and AI-driven feature extraction and delivery in GIS-compatible formats. Ceinsys_GIS_Tech_Play
Supporting Maintenance Decisions
The resulting road and asset information can support authorities in understanding:
- What assets are present
- Where those assets are located
- Their operating condition
- Where maintenance may be required
- Pavement condition and rehabilitation requirements
- Road-surface quality
- Bridge and structural condition
- Infrastructure information requiring database updates
This converts roadway data acquisition from a one-time survey exercise into a structured information base for ongoing infrastructure oversight.