Smart pharmacy management system

ABSTRACT
Pharmacy operations in many small and
medium healthcare setups continue to depend on
manual stock registers, handwritten billing records,
and experience-based procurement strategies. These
traditional approaches often result in stock
shortages, excessive inventory holding, expired
medicines, financial loss, and inefficient workforce
utilization. With the growing demand for accuracy,
automation, and data-driven decision-making in
healthcare retail, there is a pressing need for
intelligent pharmacy management solutions. This
paper presents the design and implementation of a
Smart Pharmacy Management System, developed as
a containerized full-stack web application
integrating FastAPI, React, MongoDB, and a
Machine Learning–based demand forecasting
module. The system provides real-time inventory
monitoring, automated sales and billing operations,
expiry date tracking with alert mechanisms, and
short-term demand prediction using a Linear
Regression model. Docker-based containerization
ensures platform independence, rapid deployment,
and scalability. Experimental evaluation shows that
the system significantly reduces manual workload,
improves inventory accuracy, minimizes medicine
wastage due to expiry, and enhances operational
decision making through predictive analytics. The
proposed solution is modular, extensible, and
suitable for future expansion into enterprise-level
pharmacy chains and cloud-native healthcare
systems.