A Digital Twin is a high-fidelity virtual replica of a physical object, system, or environment. It uses real-time data and advanced simulations to mirror the behavior and performance of its real-world counterpart. By integrating technologies such as IoT (Internet of Things), AI, machine learning, and cloud computing, digital twins enable continuous monitoring, diagnostics, forecasting, and decision-making.
Track systems and assets live to detect performance issues, failures, or anomalies before they happen. Helps in predictive maintenance and operational awareness.
Digital twins help optimize resource usage, reduce downtime, and eliminate unnecessary maintenance. This leads to lower operational and lifecycle costs.
Make smarter decisions with real-time data insights to improve strategy, efficiency, and outcomes.
Manage the asset from design to
demolition, ensuring continuity and
better long-term performance.
Run “what-if” scenarios to test fire evacuation plans, space utilization, or renovation impacts before acting.
Track carbon emissions and boost sustainability with data-driven insights and compliance support.
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