AI-Driven Inventory Management System for Pharmacy Stores

DOI

10.2991/978-94-6463-738-0_83How to use a DOI?

Keywords

AI in Inventory Management; Pharmacy Stock Optimization; Predictive Analytics in Healthcare; Machine Learning in Retail; Automated Inventory Control

Abstract

It focuses on using artificial intelligence (AI) to improve inventory management in pharmacy stores. The project addresses inefficiencies in traditional systems by leveraging machine learning (ML) techniques such as time-series forecasting, regression models. The system predicts demand, optimizes stock levels, and adjusts reorder points based on historical data, seasonal trends, and local demand patterns. Key findings demonstrate that the AI-based system significantly reduces stock shortages and excess inventory compared to conventional methods. Metrics like stockout rates and inventory turnover show marked improvement, enhancing operational efficiency and customer satisfaction. The methodology includes data preprocessing, feature engineering, and evaluating algorithms like LSTM and XG Boost. While the system’s strengths lie in its predictive accuracy and operational benefits, challenges include data dependency, computational costs, and integration issues. Future work suggests real-time adaptability, explainable AI. This research underscores the transformative potential of AI in pharmacy inventory management, promising cost-effective solutions, reduced waste, and better healthcare outcomes.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Saurabh Singh Dhurwey
AU  - Praveen Kumar
AU  - Utkarsh Sendur
AU  - Apurv Verma
PY  - 2025
DA  - 2025/06/22
TI  - AI-Driven Inventory Management System for Pharmacy Stores
BT  - Proceedings of the International Conference on Advances and Applications in Artificial Intelligence (ICAAAI 2025)
PB  - Atlantis Press
SP  - 1079
EP  - 1091
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-738-0_83
DO  - 10.2991/978-94-6463-738-0_83
ID  - Dhurwey2025
ER  -