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Vansh Khandelwal
Full Stack Web Devel...ย โขย 1d
Digital twins are live virtual replicas of physical systems that combine IoT sensor data, physics- and data-driven modeling, and analytics/ML to mirror real-time conditions. Their core components are continuous data input, dynamic modeling, and predictive analytics. Use cases include manufacturing (predictive maintenance and qualityโGEโs engine twins boost uptime), healthcare (patient-specific modelsโMayo Clinic), and urban planning (Singapore). Benefits: faster, data-driven decisions, efficiency gains, and risk mitigation. Challenges: cybersecurity, integration complexity, and ongoing update/resource needs. With AI/ML advances, organizations should adopt secure, phased digital-twin strategies to optimize operations and reduce costs.
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