Container × GPU × AI Pod Platform

Next-Generation Deep Learning Perception Platform

Seeing the Real World Behind the Data

The AI Detection & Recognition System is designed for complex environments, integrating face, vehicle, behavior, and environmental event recognition with edge computing to deliver real-time and precise intelligent analytics.

Human Features

Idle resources / Unmanaged

AI DETECTION & RECOGNITION PLATFORM

AI Detection & Recognition System

Built on deep learning and multimodal perception technologies, this AI Detection & Recognition System is an intelligent perception and decision platform for complex scenes. From video and targets to events, it completes a closed-loop decision chain of detection, analysis, and feedback.

CURRENT FOCUS

Human Feature Recognition

Supports face detection, attribute analysis, and multi-target tracking for access control and people-flow management.

Human Features · PERSON MODULE

Human Feature Recognition

Through face detection, attribute analysis, and pose estimation, the system understands people distribution and behavior status in real time. It is suitable for access control, people-flow statistics, and dangerous-action recognition.

Face recognition and attribute analysis, including gender, mask, glasses, and upper-body clothing color.
Pedestrian detection and multi-target tracking in complex scenes.
Human pose behavior estimation supporting dangerous-action and fall recognition.

LIVE ANALYTICS

APPLICATION DOMAINS

Smart City & Public Safety Traffic Monitoring & Parking Management Industrial Sites & Factory Safety Venue / Mall / Airport People-Flow Management

MRT Station Behavior Features
AI-Powered Intelligent Event Warning

Detects key features of high-risk events in public areas. It not only identifies people, but also understands behaviors and threats.

● AI EVENT LOG System Standby

AI Case Videos

AI Deployment Field Cases

From people-flow detection and traffic management to smart-site deployment, AI recognition videos demonstrate detection performance and operational value after Edge / CMS integration with field systems.