ICAS: Intelligent Canteen Automation System - An AI Based Approach for Smarter Canteen Operations

Abstract

University canteens face daily challenges that affect hundreds of students — long queues, food wastage, and no structured way for students to share feedback. This paper presents ICAS (Intelligent Canteen Automation System), a web-based platform built using HTML, CSS, and JavaScript that addresses these challenges in a simple and practical way. ICAS provides online food ordering with Dine-In and Takeaway modes, a token-based queue system, and two AI features: Queue Prediction for students and Demand Forecasting for canteen staff. A Best Dish of the Day voting feature allows students to rate their ordered dishes, with results shown on a live leaderboard. ICAS is lightweight, browser-based, and deployable without complex server infrastructure, making it well-suited for any college or university canteen.

Introduction

ICAS is a web-based canteen management system developed to address common problems in college canteens, including long queues, food wastage, and the lack of student feedback mechanisms. Traditional canteens rely on manual ordering and cash payments, causing delays and inefficiencies, especially during peak lunch hours.

The system allows students to log in, browse a digital menu, select either Dine-In or Takeaway, place orders online, and receive a digital token number after payment. A Queue Prediction feature estimates waiting times based on pending orders and preparation times, helping students manage their schedules more effectively.

For canteen staff, ICAS provides an Admin Dashboard that displays real-time order status and includes a Demand Forecasting module. Using an exponential smoothing technique, the system predicts the quantity of each food item needed for the next day, reducing food wastage and improving inventory planning.

Another unique feature is the Best Dish of the Day Voting System, where students can vote for their favorite dish after receiving their order. This helps management understand customer preferences and improve menu offerings.

Literature Review Highlights

Previous canteen management systems offered features such as online ordering, digital payments, token queues, and demand prediction. However, most lacked one or more of the following:

• Dine-In and Takeaway options
• Queue wait-time prediction
• Student feedback and voting
• Integrated demand forecasting

ICAS combines all these features into a single platform, making it more comprehensive than existing solutions.

System Architecture

The system follows a three-layer architecture:

1. Presentation Layer
   • Built using HTML5, CSS3, and JavaScript.
   • Provides interfaces for students and staff.
2. Application Logic Layer
   • Handles authentication, menu management, ordering, queue prediction, forecasting, and voting through JavaScript modules.
3. Data Layer
   • Uses REST APIs and JSON-based storage for menus, orders, votes, and forecasting data.

Key Benefits

• Reduces physical queues and waiting time.
• Improves user convenience through digital ordering.
• Minimizes food wastage via demand forecasting.
• Enhances student engagement through dish voting.
• Provides efficient order and inventory management for canteen staff.

Conclusion

This paper presented ICAS, an Intelligent Canteen Automation System that brings together five practical features to improve the daily experience of students and canteen staff: a digital menu with Dine-In and Takeaway mode selection, a token-based queue system, an AI powered queue prediction feature, a demand forecasting dashboard for staff, and a Best Dish of the Day voting and leaderboard system. The system is built using HTML, CSS, and JavaScript — technologies that are lightweight, widely supported, and easy to maintain. ICAS does not require a complex server or expensive infrastructure, which makes it practical for deployment in any college or university canteen. The screenshot walkthrough shows that ICAS covers the complete journey of a canteen user, from login to ordering, token collection, and post-order feedback. The admin side gives canteen staff everything they need to manage orders in real time and plan the next day\'s food supply using AI-generated forecasts. Future improvements will include the integration of smart digital display boards at canteen counters to show real-time token status, wait times, and menu availability, along with the development of dedicated Android and iOS mobile applications to enhance accessibility. Additionally, dietary filters such as vegetarian, vegan, and allergen-based options will be introduced to cater to diverse user preferences and requirements, along with the integration of a customized menu request feature to allow users to suggest or personalize meal options.

References

[1] M. Mukesh Krishnan, S. Avudaiappan, S. Mohamed Anees, and L. Thirumaran, \"Canteen Food Ordering System and Management,\" International Research Journal of Engineering and Technology (IRJET), vol. 08, no. 03, pp. 1672–1674, Mar. 2021. [2] S. Nikhil, P. Hemanth, T. Vikas Vardhan, and S. Mekala, \"Canteen Automation System Using Android,\" International Journal for Research in Applied Science & Engineering Technology (IJRASET), vol. 10, no. VI, Jun. 2022. [3] A. Kulkarni, S. H. Pisal, N. N. Patil, R. S. Waghmare, and Y. D. Kumbhar, \"Smart Serve Cafeteria Automation for Efficiency and Experience,\" International Journal of Innovative Research in Technology (IJIRT), vol. 11, no. 6, pp. 140–145, Nov. 2024. [4] B. Tejasri, D. Vinay Kumar, G. Prasad, K. Deeksha, CH. Devi, and S. KrishnaDeepika, \"Intelligent Canteen Management Using Machine Learning for Real-Time Ordering and Sustainable Operations,\" International Journal of Innovative Research in Technology (IJIRT), vol. 11, no. 11, pp. 5295–5302, Apr. 2025. [5] A. Binu, A. S. Adithya, A. Santhosh, T. S. Thamara, and K. Pradosha, \"E-Treat: Smart Canteen Automation System — A PHP and MySQL Based Web Application,\" International Journal of Scientific Development and Research (IJSDR), vol. 10, no. 11, Nov. 2025. [6] S. J. Kampli, A. S. Y. Amogh, O. D. Arvadiya, A. V. Hosatti, and A. R. S. P. Ajay, \"CampoBite: Smart Canteen Management System for Campus Canteens,\" International Journal of Emerging Trends in Engineering and Development (IJETED), vol. 16, no. 1, pp. 163–171, 2026. DOI: 10.5281/zenodo.18254670. [7] P. Sharmila, P. Pooja, V. Parinita Roshan, S. Prahathi, and S. Ranjana, \"Food Corner — Smart Canteen Ordering System,\" IRE Journals (IREV), vol. 9, no. 6, pp. 300–307, Dec. 2025. DOI: 10.64388/IREV9I6-1712570. [8] S. Biradar et al., \"Intellicater — ML Powered Canteen Management System,\" International Journal of Research Publication and Reviews (IJRPR), vol. 5, no. 5, pp. 13096–13102, May 2024. ISSN: 2582-7421. [9] T. Bhoye, S. Jedhe, S. Daphal, U. Pawar, and C. Mehetre, \"Canteen Automation System Using AI Driven Approach,\" International Journal of Novel Research and Development (IJNRD), vol. 10, no. 5, pp. a850–a859, May 2025. ISSN: 2456-4184. [10] P. Bochare, M. Bawankar, P. Auti, and V. Harane, \"Smart Canteen Automation System Using Android,\" Journal of Emerging Technologies and Innovative Research (JETIR), vol. 11, no. 5, May 2024. ISSN: 2349-5162. [11] G. Navelkar et al., \"Canteen Management System,\" International Research Journal of Engineering and Technology (IRJET), vol. 9, no. 7, Jul. 2022. [12] M. Ambika et al., \"Cashless Canteen Management System for Digital Transactions,\" International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 9, no. 7, May 2020. ISSN: 2278-3075. [13] G. Sanjana Reddy et al., \"A Web-Based Solution to Queue Management in Canteens,\" International Journal of Recent Technology and Engineering (IJRTE), vol. 12, no. 4, Apr. 2023. ISSN: 2278-0181. [14] A. Katkar and S. Jangale, \"Canteen Management System Using an E-Wallet,\" International Journal of Advance Research, Ideas and Innovations in Technology, vol. 4, no. 3, pp. 112–117, 2018. [15] E. Žuni?, \"Application of Facebook\'s Prophet Algorithm for Successful Sales Forecasting Based on Real-World Data,\" International Journal of Computer Science and Information Technology (IJCSIT), vol. 12, no. 2, Apr. 2020.

Copyright

Copyright © 2026 Rekha Kumari, Tayyaba Fatima . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.