TableTap is a final-year Android project that replaces the paper menu, the waiter's notepad and the printed bill in a dine-in restaurant. A customer scans the QR code on the table, browses the menu on their own phone, sends the order straight to the kitchen and pays a GST bill on the phone. Friends at the same table can join the same table session and order together.
Problem Statement
In busy restaurants, guests wait for a waiter to take orders, orders are misheard or lost, the kitchen has no clear queue, and bills are calculated by hand. Owners have no data on popular dishes, rush hours or customer feedback.
Proposed Solution
One Android app with two roles (customer and kitchen staff) and a PHP admin panel. The table QR opens a table session, the server re-prices every order so prices cannot be changed from the app, each order becomes a live KOT ticket on the kitchen board, and the bill is generated with CGST + SGST, coupons and loyalty rewards.
AI Features
- AI meal suggestion: enter number of people, budget and mood – Gemini picks a full meal within the budget (offline planner works without an API key; 300/300 test cases stayed within budget).
- Kitchen rush tip and feedback summary for staff and admin using Gemini, with offline fallback.
Modules
- Customer: register with taste preferences, scan table QR, menu with veg/spicy filters, dish options (half/full, spice, add-ons), cart, live order tracker, call waiter, GST bill + PDF, feedback, rewards and order history.
- Kitchen staff: live KOT board (New / Cooking / Ready), tick items, mark items sold out, tables and waiter calls, today's summary with AI rush tip.
- Admin panel: dashboard with charts, orders, menu and categories, tables with printable QR codes, staff, customers, bills, feedback, offers, notices and settings (GST, loyalty, Gemini key).
Technology
Android (Java), PHP 8 REST APIs with PDO, MySQL (15 tables), Volley, ZXing QR scanner, Android PdfDocument, Google Gemini API.
What You Get
Full Android Studio source code, PHP backend and admin panel, SQL database with realistic sample data, 55-page project report with 54 diagrams, abstract, project explanation with viva questions, setup guide and screenshots.