WaitWise is a frontend prototype of a queue congestion prediction system designed for ration shops and public distribution centers.
It allows users to:
- Predict crowd levels for specific time slots
- Adjust predictions based on group size
- Identify peak and low traffic periods
- Get best-time-to-visit recommendations
This project focuses on clean architecture, UI/UX refinement, and deployable production readiness.
https://waitwise-omega.vercel.app
Public service centers often experience unpredictable crowd surges.
Visitors waste time standing in long queues without visibility into congestion levels.
WaitWise aims to provide structured, time-based insights to help users plan visits more efficiently.
- Time-slot based crowd prediction
- Multi-shop simulation model
- Group-size adjusted congestion calculation
- Calm / Average / Crowded status classification
- Best-time recommendation engine
- Smart insights summary panel
- Responsive layout (desktop + mobile)
- Production deployment via Vercel
Frontend:
- React (Create React App)
- Component-based architecture
- Modular CSS styling
Architecture:
components/for reusable UI modulesutils/for business logic (crowd status calculation)data/for structured simulation dataset
Deployment:
- Vercel (CI/CD integrated with GitHub)
src/ │ ├── components/ │ ├── Header │ ├── HeroBlock │ ├── StatsGrid │ ├── VisitAdvisor │ ├── InsightsPanel │ ├── InfoCard │ └── SectionContainer │ ├── data/ │ └── crowdData.js │ ├── utils/ │ └── crowdUtils.js │ └── pages/ └── Dashboard.js
src/ │ ├── components/ │ ├── Header │ ├── HeroBlock │ ├── StatsGrid │ ├── VisitAdvisor │ ├── InsightsPanel │ ├── InfoCard │ └── SectionContainer │ ├── data/ │ └── crowdData.js │ ├── utils/ │ └── crowdUtils.js │ └── pages/ └── Dashboard.js
v1.0 – Portfolio Prototype Stable
This version focuses on:
- UI stability
- Core prediction logic
- Structured component architecture
- Clean production deployment
- Backend integration (Django REST API)
- Real-time crowd tracking
- Authentication and role-based access
- Admin dashboard for shop managers
- ML-based demand forecasting
- Historical analytics visualization
Advait Rathish
B.Tech Computer Science Engineering
Kerala, India
GitHub: https://github.com/advaitrathish
LinkedIn: https://www.linkedin.com/in/advaitrathish/
This project is built for portfolio and demonstration purposes.