Authors : Richardson A.; Kishore Kumar U.; Giftson Rajarathinam N.

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/yzddcb5b

Scribd : https://tinyurl.com/2v23wsyk

DOI : https://doi.org/10.38124/ijisrt/26feb887

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This research work proposes a smart food takeaway app that allows users to place orders via voice interaction on a web-based interface. The proposed system aims to enhance accessibility for differently abled users by minimizing reliance on complex visual interfaces and accurate touch interactions while ordering. The proposed app utilizes speech recognition and natural language processing algorithms to interpret user commands, assist users in navigating menu options, and finalize orders using simple voice commands. The proposed system’s responsive frontend and modular backend design facilitate safe user registration, restaurant and menu management, order placement, and real-time order status updates. The proposed system simplifies the end-to-end food ordering process and makes it accessible with minimal human intervention, thus improving convenience and independence for visually or motor-impaired users while remaining user-friendly for all customers.

Keywords : Artificial Intelligence; Food Takeaway; Voice-Based Ordering; Natural Language Processing; Recommendation System; Web Application

References :

1. J. R. Allen and M. Smith, “Voice-Based Food Ordering Systems Using Speech Recognition,” 2018.
2. L. Chen, Y. Zhang, and K. Li, “Personalized Food Recommendation Using Machine Learning Techniques,” IEEE Access, 2019.
3. Kumar and S. Patel, “Real-Time Demand Prediction in Food Ordering Platforms,” 2020.
4. R. Sharma and P. Verma, “Secure and Scalable Architecture for Cloud-Based Food Delivery Applications,” 2021.
5. T. Mikolov et al., “Advances in Neural Networks for Natural Language Processing,” 2013.