Smart Inventory Management System using LSTM

This study introduces the Smart Inventory system, designed to address traditional inventory challenges through advanced technological integration. Central to the system is the use of loT technology with RFID, enabling real-time monitoring of products, vehicles, and personnel to ensure accurate tracking and enhanced security. Leveraging machine learning, particu-larly LSTM models, the system performs sophisticated demand forecasting and inventory optimization, drawing on historical data and market trends. The integration with Odoo further streamlines inventory control, enhancing operational efficiency. By combining these technologies, the Smart Inventory system improves stock level management and customer satisfaction. Real-world case studies and performance metrics, such as Mean Absolute Percentage Error (MAPE), underscore its practical value for businesses aiming to modernize inventory management.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/miucc62295.2024.10783613
Citations
1
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
0.35
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article

Smart Inventory Management System using LSTM

Fakhriye Hamed, Noha ElMasry, Lamiaa Mostafa, Noor Essam et al.
1 citations
Smart Systems and Machine Learning
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article

Smart Inventory Management System using LSTM

Fakhriye Hamed, Noha ElMasry, Lamiaa Mostafa, Noor Essam, H. Mohammed, H. Abdelrahaman
article en
1 citations

Abstract

This study introduces the Smart Inventory system, designed to address traditional inventory challenges through advanced technological integration. Central to the system is the use of loT technology with RFID, enabling real-time monitoring of products, vehicles, and personnel to ensure accurate tracking and enhanced security. Leveraging machine learning, particu-larly LSTM models, the system performs sophisticated demand forecasting and inventory optimization, drawing on historical data and market trends. The integration with Odoo further streamlines inventory control, enhancing operational efficiency. By combining these technologies, the Smart Inventory system improves stock level management and customer satisfaction. Real-world case studies and performance metrics, such as Mean Absolute Percentage Error (MAPE), underscore its practical value for businesses aiming to modernize inventory management.

Misr International University (EG)
Openalex Percentile: Top 35%
Smart Systems and Machine Learning
0.35
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