Industrial imaging
Purpose-oriented camera and illumination arrangements capture repeatable views of defined rolling-stock inspection zones.
MACHINE VISION INSPECTION SYSTEM
Intelligent inspection
for moving rail assets.
LorGo MVIS combines industrial imaging, optical sensing, AI-assisted computer vision and inspection intelligence to transform rolling-stock examination into a repeatable, evidence-led digital workflow.
AIVision analytics
360°Multi-view inspection
LIVEInspection events
DATATraceable evidence
ACTIVE VISION SCAN
WHEEL / BOGIE
BODY SURFACE
UNDERFRAME
SYSTEMONLINE
STREAM01 / LIVE
MODEAI + OPTICAL
MVIS / RS-01
ROLLING STOCK
ROLLING STOCK
FRAME 02418
ANALYSIS RUNNING
ANALYSIS RUNNING
INSPECTION INTELLIGENCECapture → Analyse → Verify → Act
NON-CONTACT • MODULAR • EVIDENCE-DRIVEN
01 / THE PLATFORM
A digital inspection layer for rolling stock.
MVIS is designed to sit between the physical railway asset and the inspection workflow. It acquires visual and optical information, processes the data through configurable analytics and turns observations into reviewable inspection events.
Instead of treating an image as the final output, the platform is structured around the complete chain: capture, synchronize, analyse, classify, evidence, review and respond.
AI-assisted analysis
Computer-vision models can be configured for selected components, defect classes and visual patterns.
Optical sensing
Non-contact sensing can support load-profile and geometry-oriented inspection applications.
Digital evidence
Findings can be connected with imagery, timestamps, asset context and review status for traceability.
02 / ROLLING STOCK
See the inspection from the asset's perspective.
Explore what MVIS can observe across wheel, bogie, underframe, body, coupler, brake and loading zones. Each inspection class can be configured around the project requirements and approved railway criteria.
Explore Inspection GuideROLLING STOCK / MVIS
INSPECTION INTELLIGENCE
From a passing train to structured inspection evidence.
As a train passes through the engineered inspection environment, synchronized acquisition captures defined views. Software prepares the imagery, identifies relevant regions and applies configured analytics.
The output is a digital event that can be reviewed by authorized personnel. This creates a consistent foundation for inspection reporting, maintenance investigation and future analytics.
Wheel & bogie zones Underframe areas Coach body & fittings Brake-related areas Coupler interfaces Loading profile
03 / APPLICATIONS
Two focused applications.
One inspection philosophy.
MVIS can support different railway inspection problems without forcing every requirement into a single generic workflow.
Rolling Stock Inspection
Multi-view imaging and AI-assisted computer vision for systematic examination of configured rolling-stock regions, with highlighted findings and image-based evidence.
Explore applicationLoad Balance
Optical sensing and visual analysis for identifying configured load-profile and distribution abnormalities across wagons, supporting verification before operational release.
Explore application04 / WHAT MVIS CAN DETECT
Turn visual conditions into reviewable evidence.
Inspection logic can be configured around the components, zones and condition classes that matter to the project. The examples below describe inspection targets, not blanket performance claims.
ROLLING STOCK01
Component & surface conditions
Configured vision models can highlight visual indications around wheels, bogies, underframe areas, body fittings and other defined inspection zones.
LOAD BALANCE02
Uneven loading & load profile
Optical sensing and image analysis can be configured to identify loading patterns that require verification before the wagon continues through the operational process.
AI ANALYTICS03
AI-assisted visual analysis
Models can classify configured visual patterns and connect the result to the source imagery, asset context and inspection event.
05 / SYSTEM ARCHITECTURE
From railway asset to inspection decision.
MVIS treats hardware, analytics and evidence as one engineered workflow. Individual deployments can be adapted to the available site conditions, sensing channels and integration requirements.
01
Asset
Moving train / wagon enters the inspection environment.
→
02
Capture
Cameras and optical sensors acquire synchronized inspection data.
→
03
Analyse
Image processing and configured AI logic evaluate relevant regions.
→
04
Evidence
Findings are linked to imagery, timestamps and asset context.
→
05
Verify
Authorized personnel review findings and take the applicable action.
06 / OPERATIONAL VALUE
Better inspection is more than detection.
The value of MVIS comes from creating a repeatable information pipeline that helps inspection teams find, verify, document and learn from conditions across rolling stock.
Consistency
Repeatable acquisition reduces dependence on changing viewing conditions and supports standardized inspection coverage.
Traceability
Inspection events can retain the evidence and context needed for later review, investigation and reporting.
Scalability
New inspection zones, cameras, models and analytics can be introduced as the project evolves.
Human control
AI findings remain reviewable so authorized personnel can validate observations before action.
07 / START A DISCUSSION
Build a Smarter Inspection Workflow for the Future of Rail
Discuss inspection zones, defect classes, sensing requirements, integration options and deployment architecture with the MVIS team.