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

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
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article

AI for Inventory Management

A. Satish, Ch. Venkatesh, Anjana Babu, Y V Ravi Kumar et al.
Advanced Statistical Process Monitoring
article

AI for Inventory Management

A. Satish, Ch. Venkatesh, Anjana Babu, Y V Ravi Kumar, G Punith Sai, G Nagavallika, P Sunny Jaswanth
article en

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.

Openalex Percentile: Top 92%
Advanced Statistical Process Monitoring
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AI for Inventory Management — A. Satish, Ch. Venkatesh, et al. · (2025) | TGRS Research Map | TGRS