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SmartBite, a University of Central Punjab final-year project, accepted orders without integrating a payment gateway: customers transferred the exact amount to the project’s merchant bank account, uploaded proof, and waited for an administrator to verify the payment before the order advanced. That made the checkout possible for this student-built demo, but it also made payment review a manual step—not evidence that Pakistani businesses generally lack gateway access or that the approach meets the requirements of a commercial marketplace.
What SmartBite was designed to do
Software engineer Huzaifa Iftikhar describes SmartBite as a marketplace connecting home chefs, nearby customers, delivery riders, and ingredient vendors, with administrators overseeing the service. Iftikhar worked on the mobile applications and recommendation engine. The University of Central Punjab group project was advised by Dr. Rabia Tehseen and built by Abdullah Maqsood, Iftikhar, and Moizz Ahmad.
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The project used five applications sharing a backend: an Express 5 and TypeScript server with Mongoose, MongoDB, and Socket.IO; a Next.js dashboard for chefs, vendors, and administrators; an Expo and React Native app for customers and riders; a Python FastAPI recommendation service; and a public Next.js landing site. Iftikhar identifies Next.js 15, React 19, Expo SDK 54, React Native 0.81, Python 3.11, and scikit-learn among the project’s technologies.
A shared users collection let an account created on the web sign in on mobile, or vice versa. The customer and rider experiences were route groups in the same Expo project, which let the small team maintain one mobile codebase rather than separate apps.
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How checkout worked without a gateway integration
The team initially included JazzCash as an enum value, but removed that plan. In the checkout flow Iftikhar describes, the customer saw the project’s merchant IBAN and a QR code showing the exact amount due. They then opened their own banking app and sent a Raast or bank transfer. Afterward, they uploaded a screenshot or transaction receipt as proof.
An administrator checked the transfer against the bank account and approved or rejected it. The order proceeded only after approval. This replaced automated gateway confirmation with a customer-initiated transfer and a human review.
Why the team chose this route
Iftikhar says the student team could not complete the merchant onboarding process and wanted to avoid gateway API keys and monthly fees for the project. Those are the team’s stated constraints, not a finding about gateway availability or eligibility across Pakistan. The account does not establish the business, legal, accounting, fraud-control, or consumer-protection requirements that would apply to a real commercial food-delivery marketplace.
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Bank transfer made a payment flow possible without integrating a gateway, but it did not make payment confirmation automatic. An order depended on an administrator checking the account and acting on the uploaded proof. Iftikhar acknowledges that this is slower than a card payment. The project does not report measured transaction costs, fraud rates, conversion, or a comparison of commercial payment options.
How orders moved from kitchens to customers
- Chef marks the meal ready: This signals that the order can be collected.
- Dispatcher offers the job: The system offers the delivery to nearby riders.
- Rider accepts: The accepting rider becomes attached to that order.
- Rider shares location: The rider’s phone sends GPS position updates.
- Customer checks progress: According to Iftikhar, the customer app polls every 15 seconds for order status, kitchen location, and the rider’s latest position, then moves the rider pin on the map.
The team tested the flow with live requests against a running server. Iftikhar says walking through it from the rider’s perspective exposed an active-delivery screen that remained stale after an order’s status changed. He describes the lesson this way: “A system can be completely correct and still be broken for the person using it.”
What happened when supporting services were unavailable
SmartBite’s design included fallbacks so a demo could continue when an external service or reliable internet was unavailable:
- Recommendations: If the recommendation service could not be reached, the backend fell back to popularity ranking.
- Map distance: If the map integration was unavailable, the system could use straight-line distance.
These are design choices reported by the project author, not independently measured uptime or reliability results. Straight-line distance is a fallback estimate, not a substitute for a route’s actual travel distance.
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How the recommendation system handled sparse history
A new marketplace has little customer rating history to learn from. For its described live recommendations, SmartBite used meal content and popularity: it represented each meal’s name, description, and tags with TF-IDF, compared meals using cosine similarity, and used a Bayesian average to rank meals when a user had no history. Recommendations also included a plain-language reason.
The team separately experimented with collaborative filtering using the public Food.com dataset from Kaggle. Iftikhar reports filtering the data to 150,000 interactions, using 120,000 for training and 30,000 for testing, with 14,518 users, 14,972 recipes, 100 factors, and 20 epochs. The reported held-out results were RMSE 0.936, MAE 0.536, and Precision@10 0.913 at a relevance threshold of 4.0. These are results reported in Iftikhar’s 2026 account and have not been independently reproduced here; they describe the Food.com experiment, not recommendation performance for SmartBite customers.
What this project demonstrates—and what it does not
SmartBite is a student project described by a team member, not a documented commercial rollout. Its account shows one way a team handled checkout in a demo when gateway onboarding was outside its reach: accept bank transfers, collect proof, and make an administrator responsible for verification. It also shows the cost of that choice in the workflow: the order cannot move forward until someone reviews the payment.
The project’s architecture joined marketplace roles, ordering, delivery dispatch, location updates, and recommendations in a shared system. But its account does not establish whether the payment method would satisfy requirements for a live service, whether a gateway would have been available to a particular business, or how the design would perform at commercial scale.
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