Advanced International Journal for Research

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AI-Enabled Smart Restaurant Ordering and Pickup Platform

Author(s) Mr. Murali Mohan Darapureddy, Sagarika Saka, Dasari Navaneetha, Chintakuntla Lohith Rama, Chakinala Anvesh
Country India
Abstract Online food ordering has moved from a convenience to a daily habit for many urban consumers. Yet, most commercial platforms are designed around delivery and third-party logistics, which drives up service charges, introduces additional latency, and places a commission burden on restaurants. In this work, we present IntelliPick, an AI-enabled smart restaurant ordering platform that takes a different path by emphasising advance ordering and secure in-person pickup. Customers can discover nearby outlets, examine menu items with images and place orders at standard in-store prices, and collect them using a one-time password (OTP) based verification procedure. The system is built on a three-tier web architecture that combines a React front end, a Spring Boot middle tier, and a MySQL database, and is augmented with components for dish recommendation, sentiment analysis of reviews, and distance-based restaurant ranking using the Haversine formula. A prototype implementation and exper- imental study show that IntelliPick can handle core operations within a few seconds of response time while maintaining accurate proximity ranking and useful recommendation behaviour. The results suggest that a pickup-centric, AI-assisted model can offer a cost-effective and operationally simpler alternative to heavily delivery-driven food platforms for both customers and restaurants.
Keywords Online food ordering, pickup systems, restau- rant discovery, recommendation systems, sentiment analysis, Haversine distance, web applications, JWT authentication.
Field Engineering
Published In Volume 7, Issue 2, March-April 2026
Published On 2026-04-22
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E-ISSN 3048-7641
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