Why Location Intelligence and Icon Map for Rail?

Leverage your existing Power BI and Microsoft data platform infrastructure to bring advanced geospatial insights to rail operations without costly GIS licensing. Break down silos and enable reports and data sharing with partners and the public.

Leverage Existing Investments

Utilise your existing Power BI and Microsoft data platform infrastructure, eliminating the need for costly additional GIS software such as ArcGIS. Eliminate siloed access to location intelligence with organisation-wide unlimited licensing, enabling seamless sharing of reports and data with partners and the general public.

Asset Monitoring Dashboards

Visualise near real-time or historic location data on track conditions, rolling stock health, and infrastructure wear. Create holistic dashboard views to optimise maintenance schedules and reduce delays and costs.

Delay Attribution Analysis

Pinpoint recurring delay hotspots and contributing factors such as congestion or infrastructure faults. Replay journeys to show cascading effects and allocate resources effectively to reduce compensation payouts.

Environmental Factors

Analyse environmental factors affecting the rail network. Integrate 3D terrain and soil types with weather patterns and flood-prone areas to refine risk assessments.

Integrate external datasets such as National Tree Map for tree locations along tracks, enriched with metrics like height and species, to assess storm risks.

Health and Safety Monitoring

Visualise incidents across the rail network from high-level trends to station-level insights. Identify issues inside buildings or across the network, such as near-misses at level crossings.

Public Behaviour Analysis

Analyse passenger movement and flows within stations and on trains using in-house data and external sources to identify high-risk hotspots and optimise crowd management.

Asset Monitoring

Icon Map leverages GPU-enhanced visualisation to render hundreds of thousands of data-bound objects smoothly, enabling macro and micro geographical insights that were not previously possible.

Real-time Condition Monitoring

Track rolling stock performance, track conditions, and infrastructure wear using sensor and IoT data with severity-based colour coding.

Predictive Maintenance

Use AI-driven analytics to identify wear trends and anticipate component failures, highlighting high-risk areas for intervention.

Historical Analysis

Identify recurring failure hotspots and long-term degradation patterns. Combine maintenance history with failure data to refine strategies.

Impact Analysis

Overlay asset health data with service performance to reveal how infrastructure conditions contribute to delays and inefficiencies.

Integration of External Geospatial Datasets

Enhance analysis with external sources like weather, flooding, and temperature to refine risk assessment and prioritise tasks.

Optimised Maintenance Scheduling

Move from reactive to predictive maintenance by using real-world asset data to optimise scheduling based on location.

Delay Attribution Analysis

UK train operating companies collectively paid £138.6 million in passenger compensation under the Delay Repay scheme in 23/24. (gov.uk)

Enhancements in sub-minute data availability via Quartz or GPS tracking enable deeper analysis of the root causes of delays. Combine cloud-native geospatial formats with the latest GPU-enhanced visualisation frameworks to unlock insights for proactive delay management.

Realtime Monitoring

Track network performance and highlight delays as they occur with severity-based colour coding and proactive alerts.

Attribution Disputes

Generate a complete visual timeline of delays by overlaying contributing factors and replaying delays minute by minute.

Historical Analysis

Identify recurring delay hotspots and patterns to target improvements while assessing high-risk areas such as trespassing and flood-prone zones.

Impact Analysis

Overlay passenger data to assess the cost impact of delays, estimating potential vs. actual compensation costs.

Scheduling Analysis

Identify scheduling issues such as tight train spacing that increase the risk of knock-on delays.

Attribution Automation

Use AI-enhanced processes to analyse patterns and automatically attribute delays, highlighting potential dispute cases.

Customer Success Stories

Orange Concessions case study screenshot

Orange Concessions, Fibre Deployment and Commercialisation

Orange Concessions, France’s leading rural fibre operator, accelerated deployment, improved commercial targeting, and is targeting a single trusted platform for fibre operations using Icon Map Pro.

SNCB case study screenshot

Transforming Rail Safety: The Power of Location Intelligence in Action at SNCB

Safety is a cornerstone of SNCB’s operational strategy. As Belgium’s national railway operator, SNCB places significant emphasis on the safety and security of both passengers and staff.