Sai, G Punith and Nagavallika, G and Babu, A V S Sai and Satish, A and Kumar, Y Vinay and Jaswanth, P Sunny and Venkatesh, Ch (2025) AI for Inventory Management. International Journal of Innovative Science and Research Technology, 10 (4): 25apr681. pp. 1075-1081. ISSN 2456-2165

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Abstract

This project involves the development of an AI-driven inventory management system designed to simplify stock tracking and restocking for small businesses. It combines traditional inventory methods for products with stable demand and a machine learning model to predict restocking needs for items with fluctuating demand. The machine learning model is pre-trained on standard datasets, ensuring accurate forecasts without requiring training from user data. Developed using Django, MySQL, and Bootstrap, the system is web-based and accessible from any device. Key features include vendor management, automated restocking alerts via email, and a billing module for managing in-store sales. Users can categorize products, track stock levels in real time, and view a dashboard that highlights low-stock items. With a user- friendly interface and intelligent automation, this system supports small business owners in making efficient, data-driven decisions.

Item Type: Article
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Editor IJISRT Publication
Date Deposited: 25 Apr 2025 11:55
Last Modified: 25 Apr 2025 11:55
URI: https://eprint.ijisrt.org/id/eprint/570

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