Edge-based query processing systems and methods

Abstract

Capturing and processing edge data, like video feeds, enables a hierarchy of analysis, optimizing resource usage and enhancing responsiveness. Edge devices process data using computer vision (CV) models, identifying objects and events in real-time. In embodiments described herein, edge devices and intermediate devices can further refine the data, leveraging CV model output and large language models (LLMs) for contextual understanding. Queries can be posed to the system which may span content and context, with users exploring specific objects, events, or patterns detected in the video data. The processing described herein can provide deeper insights by analyzing textual descriptions, facilitating queries about temporal, spatial, or semantic context. This approach empowers diverse applications, from surveillance to smart city initiatives, by enabling users to extract actionable information tailored to their needs. Ultimately, processing edge data can increase responsiveness and reduce the amount of data needed to transmit to centralized devices for additional processing.

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