Interactive Venue Mapping & Smart Seat Selection (4See)

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Degree

Bachelor of Science (Computer Science)

Department

Department of Computer Science

School

School of Mathematics and Computer Science (SMCS)

Advisor

Dr. Syed Ali Raza, Visiting Faculty, Department of Mathematical Sciences

Keywords

Interactive Seat Maps, Smart Seat Detection, Event Booking, Computer Vision, Real-Time Concurrency, Distributed Seat Locking

Abstract

4see (Venue Maps and Smart Seats) is an interactive event-booking and venue-management platform designed to address the limitations of traditional text-based ticketing systems by providing visual seat selection and real-time venue mapping. The project aims to enable organizers to create digital venue layouts from floor-plan images, offer attendees an interactive seat-booking experience, and prevent double-booking through distributed seat management. The system integrates a React-based frontend, a Node.js/Express backend with MySQL, and a FastAPI microservice that uses OpenCV for AI-assisted seat detection. Real-time seat availability is maintained through WebSockets and a Redis-backed seat-locking mechanism. The platform supports venue creation, multi-floor layouts, automated seat mapping, category-based pricing, event management, and ticket checkout. Developed through iterative full-stack development and validated with industry feedback from Ticketwala, the project delivers an effective solution that improves booking transparency, operational efficiency, and the overall event-ticketing experience.

Tools and Technologies Used

React, TypeScript, Vite, Tailwind CSS, Shadcn UI, Radix UI, React Router, Node.js, Express.js, MySQL, Python, FastAPI, Uvicorn, OpenCV, Pillow/PIL, Redis, Multer, Vitest, Zod, PNPM, Git.

Methodology

The project followed an iterative full-stack development methodology involving requirement analysis, implementation, testing, feedback, and refinement. Regular meetings with the internal and industry supervisor ensured alignment with academic and business needs along with functional requirements. The system was developed as modular components, including authentication, venue management, event creation, seat mapping, smart seat detection, and booking. React and TypeScript were used for the frontend, Express and MySQL for backend services, and Python-based image processing for automated seat detection. Continuous testing and feedback-driven improvements resulted in a system that supports real-world event workflows, maintains data consistency, provides real-time seat availability, and delivers an intuitive booking experience.

Document Type

Restricted Access

Submission Type

BSCS Final Year Project

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