AI × Computer Vision

AI Customer Behavior Analytics System

Real-time Customer Behavior Analysis for Retail Environments

✓Multi-person Tracking – Track unlimited simultaneous customers in real time
✓17-point Pose Detection – Advanced skeletal tracking for precise behavior analysis
✓Intent Scoring 85–95% – Predict customer purchase intent with high accuracy
✓Area Heatmaps – Analyze a 3×3 grid of customer flow patterns
✓Real-time 25–30 FPS – Smooth, instant processing for live analytics

Key Features

AI-powered analytics for a comprehensive understanding of customer behavior

Multi-person Tracking

Track unlimited simultaneous customers with robust ID management and occlusion handling

17-Point Pose Detection

Advanced skeletal tracking analyzes body posture and movement patterns for deeper behavioral insights

Intent Scoring

85–95% accuracy in predicting customer purchase intent based on behavior patterns and dwell time

Area Heatmaps

3×3 grid analysis visualizes high-traffic zones and in-store customer flow patterns

Real-Time Performance

25–30 FPS processing delivers smooth, instant analysis with no lag and high-precision tracking.

Analytics Dashboard

Comprehensive real-time dashboard with traffic statistics, heatmaps, and customer insights

Technical Specifications

Enterprise-grade technology stack for reliable, high-performance analytics

AI Model	YOLOv8-Pose with custom fine-tuning for retail environments
Tracking Algorithm	Kalman Filter with DeepSORT for robust multi-person tracking
Computer Vision	OpenCV 4.9+ with GPU acceleration support
Programming	C++17 for high-performance real-time processing
Platform Support	Windows, Linux, NVIDIA Jetson (ARM-based edge devices)
GPU Requirement	NVIDIA GPU with CUDA support (GTX 1060 or above recommended)
Camera Compatibility	IP Cameras (RTSP), USB cameras, video file input
Data Output	CSV reports, heatmap images, real-ti

Real-World Applications

Proven solutions delivering measurable ROI in retail environments

Retail Stores

Optimize product placement and store layout based on customer traffic, identify high-engagement zones, and increase conversion rates with data-driven decision-making.

Shopping Malls

Analyze foot traffic across multiple floors and zones. Measure tenant store performance, optimize promotional activities, and improve overall traffic flow.

Convenience Stores

Monitor peak hours and customer flow in compact retail spaces to optimize staff scheduling, allocate resources effectively, and improve service efficiency and checkout speed.

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