Classification
What is Classification?
Classification in Edge AI is the process of categorizing data into predefined groups or labels using on-device machine learning models. Also known as data labeling or categorization, classification enables real-time, localized decision-making without sending data to the cloud.
Why Is It Used?
Classification is used to quickly interpret sensor data, images, video, or signals at the edge, improving speed, reducing latency, and enhancing privacy by minimizing cloud dependency.
How Is It Used?
Edge devices employ classification models to identify objects, detect anomalies, or categorize inputs in industries like IoT, smart cameras, and autonomous systems. Data is processed directly on the device for instant insights.
Types of Classification
Binary Classification: Sorting data into two categories (e.g., defective vs. non-defective).
Multi-class Classification: Assigning data to one of multiple categories (e.g., types of equipment faults).
Multi-label Classification: Tagging data with multiple labels simultaneously (e.g., recognizing multiple objects in an image).
Benefits of Classification
Real-time decisions: Instant data insights without cloud delays.
Enhanced privacy: Sensitive data remains on-device.
Bandwidth efficiency: Reduces the need for large data transfers.
Scalability: Supports distributed Edge AI deployments efficiently.