Metadata
What is Metadata?
Metadata is structured information that describes, organizes, and contextualizes data collected by Edge AI devices. Also called “data descriptors,” metadata makes raw sensor data, video feeds, or IoT streams understandable and actionable for faster processing and insights at the edge.
Why Is It Used?
Metadata enables devices and systems to interpret and prioritize data efficiently, reducing latency and optimizing storage while improving decision-making in real-time Edge AI environments.
How Is It Used?
Labeling and categorizing sensor data
Enhancing AI model accuracy by providing context
Streamlining data transfer from edge devices to the cloud
Supporting predictive analytics and automated decision-making
Types of Metadata
Descriptive: Information about data content, e.g., timestamps, location, device type
Structural: Describes how data is organized, e.g., file formats, schemas
Administrative: Details for data management, e.g., access permissions, processing history
Benefits of Metadata
Faster, real-time insights at the edge
Reduced bandwidth and storage costs
Improved AI decision accuracy
Enhanced data governance and compliance