Networks are vast, defects appear fast, and prioritisation is guesswork. Road authorities are flying blind between scheduled surveys.
Road networks span thousands of kilometres. Manual survey cycles are too slow to keep pace with defect formation and deterioration.
Potholes and surface cracking can develop between survey intervals, leaving hazards undetected until they cause damage or injury.
Manual inspection quality varies between crews, weather conditions and observer judgement, making defect trending unreliable.
Without consistent condition data, maintenance scheduling is reactive rather than risk-based, wasting budget and missing critical sites.
Vehicle-mounted camera systems capture road surface imagery as vehicles traverse the network, with no dedicated survey vehicles required.
NXTGEN Inspect AI detects and classifies potholes, cracking, rutting and surface degradation in real time from the captured imagery.
Every detected defect is mapped to GPS coordinates with severity scoring, building a continuously updated condition picture of the network.
AI analysis generates a ranked maintenance schedule, highest severity defects first, with location and evidence attached.
Detected by size, depth profile and location with severity classification
Longitudinal, transverse and alligator cracking patterns across the carriageway
Wheel-track deformation and surface depressions indicating structural failure
Ravelling, stripping and loss of surface texture across pavement sections
Pavement edge deterioration and shoulder separation
Existing patch performance and failure detection for maintenance prioritisation
Vehicle-mounted systems cover the network continuously without dedicated survey personnel or lane closures.
Every road surveyed on every traverse, no sections missed, no gaps in condition data between scheduled cycles.
Every defect mapped to exact GPS coordinates with AI-assigned severity classification and photographic evidence.
Maintenance teams receive a ranked work list, highest risk defects first, with location and evidence ready for crews.
We scope your road network, review existing condition data and configure the platform to your defect classification standards and reporting requirements.
Camera systems are commissioned to your vehicles. AI models are calibrated to your pavement types, surface materials and local defect definitions.
Continuous defect mapping begins from the first traverse. Your operations team receives live condition updates and a prioritised maintenance schedule. AI models are tuned continuously as new traverses come in, so detection keeps improving over time.
See how NXTGEN Inspect detected and mapped road surface defects across a live road network, from system commissioning to operational defect reporting.
Tell us about your road network and inspection requirements.
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