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Product Manager for Professional Visualization at PNY Technologies EMEA.
The real power of a digital twin lies in its interactivity.
This simulation capability, coupled with real-time data, provides a dynamic environment for experimentation and optimization.
This predictive capability helps organizations shift from reactive to proactive maintenance, reducing costs and avoiding unexpected downtime.
AIcan also help with anomaly detection, identifying unusual behavior patterns in the data.
One of the most significant is data management.
Integrating a digital twin with existing, sometimes outdated, systems can also be challenging.
Legacy infrastructure isnt always compatible with modern digital twins, necessitating extensive adjustments and integrations.
Another challenge is the high initial cost.
Developing a digital twin, especially for complex systems, involves significant investment.
This includes installing sensors, building models, integrating AI capabilities, and ensuringcybersecurity.
The initial expense can be a barrier for smaller organizations or those with tight budgets.
Cybersecurity is another critical concern.
Digital twins rely on a constant flow of data, often transmitted through the internet or other networks.
This data transmission can become a vulnerability, exposing the twin to potential cyber threats if not adequately secured.
Keeping a digital twin accurate over time also requires continuous maintenance.
Conclusion
Digital twins are revolutionizing industries by creating a bridge between the physical and digital worlds.
However, they also come with challenges, from high initial costs to cybersecurity concerns.
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The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
