Edge Computing: Processing Data Where It Happens

Edge computing is a distributed computing approach that moves data processing closer to the source where data is generated. Instead of sending all information to centralized cloud servers, edge systems analyze and filter data locally, reducing latency and bandwidth usage.

This model is particularly useful in scenarios where real-time response matters, such as industrial automation, smart cities, and Internet of Things devices. By handling time-sensitive tasks at the edge, systems can respond faster and continue operating even with limited connectivity. Edge computing doesn’t replace the cloud but works alongside it, balancing efficiency, reliability, and scalability. --- Source: Wikipedia The term began being used in the 1990s to describe content delivery networks—these were used to deliver website and video content from servers located near users. In the early 2000s, these systems expanded their scope to hosting other applications, leading to early edge computing services. These services could do things like find dealers, manage shopping carts, gather real-time data, and place ads. ---

Digital Twins: Simulating Real-World Systems

A digital twin is a virtual representation of a physical object, system, or process that mirrors its real-world counterpart through data. By continuously updating the model with sensor input and operational data, digital twins allow organizations to monitor performance, test scenarios, and predict outcomes without interfering with the actual system.

They are commonly used in manufacturing, infrastructure management, and product design to improve decision-making and reduce risk. Rather than serving as static models, digital twins evolve over time, providing a structured way to analyze complex systems and understand how changes impact real-world behavior.

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