Gen AI based Catering Management System


Authors : D. Nirmala; Dhanush Kumar B; Pradeep S; Buvanesh Kumar S; Sridhar R

Volume/Issue : Volume 9 - 2024, Issue 12 - December

Google Scholar : https://tinyurl.com/4twrkczf

Scribd : https://tinyurl.com/44em7rsk

DOI : https://doi.org/10.5281/zenodo.14414343

Abstract : The catering industry continues to face inefficiencies due to outdated manual processes and fragmented management systems. Traditional methods, such as using printed brochures for product selection, often result in poor consumer experiences, limited information, and increased operational costs. To address these issues, this study proposes an advanced online catering management system leveraging generative AI technology. The platform offers users access to detailed product information, dynamic menu customization, and seamless order processing. Developed using PHP, CodeIgniter, and MySQL, and validated with Black Box Testing, the system also incorporates predictive analytics for inventory optimization. By minimizing waste and enhancing customer satisfaction, the proposed platform transforms catering operations into a cost-effective, scalable, and user-centric model.

Keywords : Catering Management, AI-Driven Optimization, Inventory Forecasting, Online Ordering Systems.

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The catering industry continues to face inefficiencies due to outdated manual processes and fragmented management systems. Traditional methods, such as using printed brochures for product selection, often result in poor consumer experiences, limited information, and increased operational costs. To address these issues, this study proposes an advanced online catering management system leveraging generative AI technology. The platform offers users access to detailed product information, dynamic menu customization, and seamless order processing. Developed using PHP, CodeIgniter, and MySQL, and validated with Black Box Testing, the system also incorporates predictive analytics for inventory optimization. By minimizing waste and enhancing customer satisfaction, the proposed platform transforms catering operations into a cost-effective, scalable, and user-centric model.

Keywords : Catering Management, AI-Driven Optimization, Inventory Forecasting, Online Ordering Systems.

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