RetailEye Insights ā AI-Powered Retail Analytics & Live Monitoring Platform
Overview
RetailEye Insights is a real-time retail intelligence platform developed for GMR Hyderabad International Airport to help retailers understand customer behaviour, monitor store activity, and make data-driven business decisions using AI-powered video analytics.
The platform aggregates data from multiple cameras across retail stores and presents actionable insights through an interactive dashboard, enabling store managers and administrators to monitor footfall, customer demographics, occupancy, and live activity from a centralized interface.
My Role
Frontend Developer (React.js)
I was responsible for designing and developing the complete frontend application, integrating real-time APIs, building reusable UI components, optimizing performance, and creating interactive analytics dashboards for enterprise users.
Key Features
š Real-Time Analytics Dashboard
Developed an interactive analytics dashboard that provides:
Live footfall tracking
Customer entry and exit statistics
Hourly traffic trends
Store-wise analytics
Peak business hours
Occupancy monitoring
Real-time KPI cards
Historical trend analysis
š„ Customer Demographics
Implemented AI-powered demographic visualizations including
Gender distribution
Age group classification
Customer segmentation
Hourly demographic trends
Comparative analytics
These insights help retailers understand customer behaviour and optimize staffing and marketing strategies.
š„ Live Camera Monitoring
Built live monitoring interfaces allowing administrators to:
View multiple camera feeds
Monitor stores in real time
Switch between camera locations
Observe customer activity instantly
Access centralized surveillance dashboards
š Interactive Data Visualization
Created responsive and interactive charts for:
Footfall over time
Gender trends
Age distribution
Customer activity
Historical reports
Features include:
Dynamic filtering
Hover tooltips
Responsive layouts
Smooth chart animations
š¬ Multi-Store Management
Implemented support for multiple retail locations with:
Store selection
Centralized monitoring
Individual store analytics
Cross-store comparison
Unified management dashboard
š AI Person Tracking & Debug Console
Developed an advanced debugging interface for AI detection pipelines that displays:
Active tracking sessions
Identified and unidentified persons
Face detection quality
Re-identification confidence
Tracking lifecycle
Camera pipeline status
Frame statistics
Live processing information
This interface significantly improved monitoring and debugging of the AI vision system during development.
š¤ User & Access Management
Implemented secure administrative modules for:
User management
Role-based access
Authentication
Administrative controls
Secure dashboard access
Technical Highlights
Developed a scalable component-based architecture
Integrated REST APIs with real-time polling
Optimized rendering performance for large datasets
Built reusable UI components
Implemented responsive layouts for enterprise users
Managed application state efficiently
Created modular analytics widgets
Improved dashboard loading and rendering performance
Frontend Tech Stack
React.js
TypeScript
Tailwind CSS
React Query
REST APIs
Chart.js / Recharts (Analytics Visualizations)
Material UI
Responsive UI Design
Backend Tech Stack
Python
FastAPI
PostgreSQL
SQLAlchemy
JWT
YOLOv8
InsightFace
TorchReID
OpenCV
ONNX Runtime
MinIO
Outcome
RetailEye Insights provides retailers with real-time visibility into customer behaviour through AI-powered video analytics, helping improve operational efficiency, optimize staffing, understand shopper demographics, and make informed business decisions across multiple retail locations.
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