Edge
What is Edge?
Edge, or edge computing, is the practice of processing data locally on devices rather than sending it to centralized cloud servers. In Edge AI, this allows AI algorithms to analyze information in real time, enabling faster, more efficient decisions at the device level.
Why Is It Used?
Edge is used to reduce latency, improve security, and handle large volumes of data generated by IoT devices without overloading cloud systems. It brings intelligence closer to where data is created, making operations faster and more responsive.
How Is It Used?
Edge computing powers applications like autonomous vehicles, smart factories, and retail analytics. AI models run directly on edge devices, enabling real-time insights, predictive maintenance, and local decision-making.
Types of Edge
On-Device Edge AI: Computation occurs entirely on sensors or devices.
Edge Gateway: A local hub aggregates and processes data before sending it to the cloud.
Hybrid Edge: Combines on-device processing with cloud analytics for advanced AI operations.
Benefits of Edge
Reduced Latency: Real-time decision-making without cloud delays.
Enhanced Security: Sensitive data stays local, minimizing breach risks.
Bandwidth Efficiency: Less data sent to the cloud saves network resources.
Scalability: Easily integrates with distributed IoT networks.