Rail corridors are long, linear, and difficult to inspect at scale. Twinworks enables regular, systematic corridor collection and AI-assisted analysis — so you know what's changed, where encroachments exist, and what requires attention.
Rail rights-of-way are large, complex, and difficult to keep current with traditional inspection methods.
Structures, vegetation, and activities encroach on rail rights-of-way continuously. Without regular inspection, these go undetected until they become safety or compliance issues.
Traditional inspection programmes cannot economically cover entire corridors at the frequency conditions demand. Gaps in coverage create risk.
Inspection outputs based on verbal or written field notes are hard to verify, difficult to compare over time, and weak as compliance evidence.
Twinworks enables cost-effective, repeatable corridor collection. A vehicle or rail-mounted Mosaic camera captures complete 360° coverage of the alignment. AI models then analyse the imagery for encroachments, vegetation risks, structural changes, and other conditions of interest.
Complete corridor coverage
360° imagery captures every metre of the corridor from both sides — no gaps, no missed sections.
AI encroachment detection
Automated analysis flags new structures, vegetation, and activities within the right-of-way boundary.
Change detection between passes
Compare current collection against previous imagery to isolate what is new, changed, or resolved.
Defensible inspection records
Every finding is anchored to dated imagery with GPS position — strong evidence for compliance and enforcement.
Greater corridor awareness
Know what exists within the right-of-way at all times, not just after formal inspections.
Faster encroachment response
Detect issues earlier and resolve them before they escalate into safety or legal problems.
Reduced inspection cost per kilometre
Vehicle-driven collection replaces expensive walked inspections across long alignments.
Compliance-ready documentation
Dated imagery and structured outputs create a robust audit trail for regulatory purposes.
Vehicle-mounted or rail-mounted 360° cameras can be driven along corridor alignments to collect imagery at regular intervals. AI change detection models compare current imagery against baseline datasets to flag new encroachments, vegetation changes, structural concerns, or access issues — without requiring crews to walk every metre of track.
Corridor intelligence refers to the ongoing process of understanding what exists within a rail right-of-way, what has changed since the last observation, and what conditions may present risk or compliance issues. It combines regular imagery collection with AI-assisted analysis to maintain a current, structured picture of corridor conditions.
Each collection pass creates a georeferenced imagery dataset anchored to GPS positions. The Twinworks platform compares successive passes at matching positions, enabling analysts and AI models to identify what is new, changed, or resolved. This creates a repeatable, evidence-based change record for the corridor.
Schedule a conversation. We'll show you how rail teams are using Twinworks to maintain corridor certainty at a fraction of traditional inspection costs.
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