RetailEye Insights – 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

📊 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

👥 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.

🎥 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

📈 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

🏬 Multi-Store Management

Implemented support for multiple retail locations with: Store selection Centralized monitoring Individual store analytics Cross-store comparison Unified management dashboard

🔍 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.

👤 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.