AI for Inventory Management
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.
Authors
- A. Satish
- Ch. Venkatesh
- Anjana Babu
- Y V Ravi Kumar (ORCID: https://orcid.org/0009-0001-2888-3867)
- G Punith Sai
- G Nagavallika
- P Sunny Jaswanth
Publication Details
- Published
- 2025-04-24
- DOI
- https://doi.org/10.38124/ijisrt/25apr681
- Primary Topic
- Advanced Statistical Process Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00