Editing User:Farhan (section)

===='''Benefits:'''====
* Real-Time Monitoring,
* Predictive Analytics & Maintenance
* Virtual Experimentation
* Enhanced Decision-Making
* Enhanced Decision-Making

This foundation makes it easy to later explore where digital twins should be deployed (edge vs cloud), based on '''latency, bandwidth, data sensitivity''', and '''computational demand'''.


Digital twins are virtual representations of physical objects that are regularly updated with real-time data so as to replicate, predict, and maximize functionality. Digital twins are increasingly applied in manufacturing, healthcare, and smart city projects that enable intelligent cities, where predictive maintenance and systems optimization can be realized.

Digital twins connect physical devices with virtual spaces. Digital twins are run at edge nodes in edge computing to carry out local processing of information to minimize the necessity to send colossal amounts of data to the cloud. The configuration is especially applicable in cases requiring real-time analytics, for example, industrial automation and healthcare monitoring.

'''Diagram 1: Digital Twin Edge Network Architecture'''
[[File:Intro_to_edge.png|500px|thumb|center|Real-Time Edge Adoption]]

This diagram illustrates a layered architecture where virtual twins communicate with physical IoT devices through edge nodes. It showcases intelligent transportation systems, 6G networks, and IoT applications as part of a hierarchical edge-cloud framework.

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