Machine Learning-Driven Optimization of Automated Dispensing Machines in Hospital Environments

Project Details

• Student(s): Christina Saliba
• Advisor(s): Dr. Pierette Zouein
• Department: Industrial & Mechanical
• Academic Year(s): 2024-2025

Abstract

Efficient inventory management and optimized storage systems are the backbone of medication systems in healthcare facilities. A robust system allows for an error-free and responsive process, which directly influences patient care outcomes. However, traditional inventory methods lack the flexibility required to adapt to such a fast-changing environment. The unpredictable demand fluctuations pose great limitations and raise concerns. This research explores the integration of artificial intelligence and machine learning with Automated Drug Dispensing Machines as a solution to streamline drug supply chains within hospitals.