Utilities
Digital Twins for Water Utilities
For water utilities, digital twins address operational efficiency, reduce maintenance costs, enhance resource management, and support sustainability efforts.
Leak Detection and Prevention
Simulate the entire water distribution system and use real-time data from sensors to detect pressure changes and anomalies. This helps in identifying leaks early and prioritizing repair actions. The system can also simulate different scenarios to predict future failures.
Demand Forecasting and Supply Optimization
Forecast water demand by analyzing data from weather patterns, usage history, and population trends. This enables real-time adjustments in water supply, helping to optimize pumping schedules and water distribution.
Predictive Maintenance for Pumps and Equipment
Monitor the performance of pumps and other equipment by collecting data on vibration, temperature, and flow rates. Machine learning algorithms can predict potential failures before they occur, enabling preemptive maintenance.
Water Quality Monitoring and Management
A digital twin integrates data from various water quality sensors that measure parameters like pH, turbidity, and chemical levels. It can simulate how contaminants might spread, enabling rapid response to water quality issues and ensuring compliance with safety standards..
Plan maintenance activities more efficiently by leveraging data-driven insights, simulations, and predictive analytics
Predict when the pump is most likely to need maintenance based on its operational data.
Simulate the effects of taking assets offline, including impacts on water pressure and regional supply.
Identify maintenance opportunities such as low demand hours and rerouting water from neighboring zones that minimize disruption.
Plan resources for maintenance, ensuring all necessary personnel, equipment, and materials are available.
Communicate maintenance plans to ensure customers are aware in advance of service interruptions.
Digital Twins and Electricity Utilities
Monitor the performance of electricity transmission and distribution assets and inform predictive maintenance.
Real-time data from sensors can help reduce downtime and extend the life of the asset.
Real-time data from sensors can help reduce downtime and extend the life of the asset.
Predictive Asset Maintenance
Monitor the condition of critical assets to predict equipment failures.
A proactive maintenance approach reduces downtime, minimizes repair costs, and extends the lifespan of assets.
Renewable Energy
Model the impact of integrating renewable energy sources into the grid.
Simulate scenarios to optimize energy storage and distribution and balance supply and demand while maintaining grid stability.
Grid Management
Integrate real-time data to monitor grid performance, identify outages or anomalies, and optimize energy distribution.
By simulating different load conditions, operators can improve reliability and efficiency.
Demand Forecasting
Analyze consumption patterns and smart meter data to improve demand forecasting accuracy.
This allows for better planning of energy generation and distribution, leading to more efficient resource allocation and reduced operational costs.
Provide a comprehensive view of the entire lifecycle of utility assets
Asset Lifecycle Management: Integrate design, construction, operation, and maintenance data to make informed decisions about upgrades, replacements, and decommissioning, optimizing asset performance and lifespan.
Condition-Based Monitoring: Monitor the health of assets from real-time data. Power condition-based maintenance strategies, where maintenance is performed based on the actual condition of equipment rather than on a fixed schedule.
Failure Prediction and Risk Management: Simulate various operational scenarios and analyze historical performance data to identify potential failure points of assets. A proactive approach enables better risk management strategies, helping to prevent outages and improve overall grid reliability.
Digital Twins and Gas Utilities
For gas transmission and distribution utilities, digital twins can be used across asset performance management, risk assessment, and integrity management to provide insights into reducing risks.
Pipeline Integrity Monitoring
Real-time models of gas pipelines, integrating data from sensors that monitor pressure, temperature, and flow rates.
Detect leaks or anomalies early, enabling proactive maintenance and ensuring the safety and integrity of pipeline infrastructure.
Predictive Maintenance
Track the performance and condition of gas critical assets to help predict equipment failures.
A predictive maintenance approach reduces unplanned outages and minimizes repair costs by allowing for timely interventions based on actual asset conditions.
Compliance & Reporting
Streamline compliance with safety and environmental regulations by maintaining an accurate digital record of asset conditions, inspections, and maintenance activities.
Gas utilities can generate reports more efficiently and ensure adherence to regulatory standards, improving overall operational transparency.
Asset Lifecycle Optimization
Modeling the entire lifecycle of gas assets—from design and construction to operation and decommissioning—utilities can make informed decisions regarding upgrades and replacements.
A comprehensive view helps optimize resource allocation and improve the long-term performance and sustainability of gas infrastructure.
Identify problematic equipment that can cause unplanned downtime
Pipeline Maintenance Strategies: Digital, dynamic models of gas distribution pipelines that incorporate real-time data from sensors that monitor pressure, temperature, and flow rates, allow gas utilities to detect leaks or abnormal conditions promptly, facilitating targeted maintenance efforts and reducing the risk of hazardous incidents.
Regulatory Compliance & Asset Tracking: Tracking of gas assets throughout their lifecycle, documenting inspections, maintenance activities, and compliance with regulatory standards. This digital record streamlines reporting processes and ensures that utilities meet safety and environmental regulations, enhancing transparency and accountability in asset management.
Digital Twins and Telecommunications
Digital twins of mobile mast and fixed line and broadband network assets allow engineers to manage, visualise and strategize network maintenance, improvements and expansion.
Site
Digital Twin
Engineering teams can eliminate site visits with access to complete structure data, including high-fidelity 3D geospatial models
Maintenance and operations teams can use it to capture more accurate asset data to support modification, repair and regulatory requirements.
Subscriber Digital Twin
High-resolution, intricate models of urban and indoor environments, including bridges, tunnels, foliage, and detailed surface materials that affect radio frequency propagation. This also encompasses user mobility and dynamic scene elements, such as vehicular traffic.
Modelling Assets
A Window into Tower Assets
TODO Water Quality Monitoring and Management
A digital twin integrates data from various water quality sensors that measure parameters like pH, turbidity, and chemical levels. It can simulate how contaminants might spread, enabling rapid response to water quality issues and ensuring compliance with safety standards..
Data Integration
Combine static and dynamic, spatial and non-spatial data together.
Drag and drop file importing
Connectors to ArcGIS, Maximo and other enterprise systems
API tools to build your own microservice connectors
Tools to build connections to IoT data sources
Hotspot link 3D models with 2D diagrams and drawings
Industry Use Cases
Rail - Rolling Stock, Network & Stations - Visual Asset Management v2
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