Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Padmavathy, M.; Dharmendra, H.; Thilagavathi, K.; Naresh, Burri; Devi, P. Praba; Tiwari, Mohit Title A name given to the resource AI-Driven Predictive Analytics for Sustainable Restaurant Operations and Waste Minimization Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Proceedings of 2025 10th International Conference on Science Technology, Engineering and Mathematics, ICONSTEM 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICONSTEM65670.2025.11374322" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICONSTEM65670.2025.11374322</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034494730?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034494730?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Padmavathy M., SRM Institute of Science &amp; Technology, Department of Commerce, Tamil Nadu, Chennai, India; Dharmendra H., CHRIST (Deemed to Be University), Department of Commerce, Bangalore, India; Thilagavathi K., Saveetha School of Law, SIMATS, Department of Commerce, Saveetha University, Tamil Nadu, Chennai, India; Naresh B., CVR College of Engineering, Department of CSE(CS), Telangana, Hyderabad, India; Devi P.P., Sona College of Technology, Department of Management Studies, Tamil Nadu, Salem, India; Tiwari M., Bharati Vidyapeeth's College of Engineering, Department of Computer Science and Engineering, Delhi, India Description An account of the resource There is mounting pressure in the restaurant business to minimize the waste of their operations and use of resources, and still be able to make a profit. Unreasonable forecasting, over-procurement, and poor management of resources are the key causes of environmental and financial waste. As a potential solution to the issue, it presents an AI-based Predictive Analytics Framework (AID-PAF), which combines both a Temporal-Fusion Neural Architecture (TFNA), which is an asset demand prediction framework, and a waste-conscious linear programming model used to solve an inventory and resources allocation problem. Real restaurant operational datasets were used to test the system in a hybrid AnyLogic-MATLAB simulator. Experimental findings show that the proposed framework achieved 40%, 18%, 15%, and 21% reductions in the food waste, energy use, water use, and costs, respectively, and in addition enhanced the accuracy of the forecast, MAPE of 6.5%, the customer fill-rate 96.2%, and the Sustainability Score 78.7. The results prove that predictive analytics based on AI can greatly contribute to the sustainability, efficiency, and profitability of restaurant operations by making intelligent decisions with the assistance of data. 2025 IEEE. Subject The topic of the resource AI-Driven Predictive Analytics Framework; Sustainability-Driven Resource Utilization Model; Temporal-Fusion Neural Architecture; Waste Reduction Rate Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156187-1; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online