Advancements In Edge AI Ushering Evolution In Video Analytics

Rapid developments in edge AI pave the pathway for dramatically improved intelligent video analytics by enhancing on-device capabilities and reducing dependency on complex IT backends.

The current landscape is changing significantly with enhanced capabilities of edge devices such as surveillance cameras and other AI-enabled edge-based endpoints. The state-of-the-art equipment comes with embedded detectors to detect, track and analyze any moving objects. These devices have the capability to detect false alarms and suppress them in a time-sensitive manner.

Such scene analysis, comprising of identification and classification of objects by edge-based devices, has inherently been poor, marred by low-quality detection and unreliable alerts. But today, these edge devices are equipped with powerful computing and run on neural networks with thousands of frames per second.

Today’s advanced devices come with numerous capabilities such as detecting, loitering, object detection, object count, object classification, speed detection, ANPR (Auto Number Plate Recognition), wrong direction driving, PPE detection, helmet detection, object filtration based on size, speed, direction and color, and much more.

Building the Foundational Blocks with Next-Gen AI

Significant improvements in the quality and quantity of the output delivered by video tools are driven by a generational leap in the new edge AI’s computational efficiency and…