2025_EML Capstone Projects

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track inventory levels, generate reorder alerts, and provide reporting capabilities (Anand & Kumar, 2022). Another alternative is a Cloud-Based Inventory Management System , which offers flexibility and scalability, allowing for real-time access to inventory data from anywhere. This system would include features for automated tracking, analytics, and integration with suppliers for streamlined ordering processes (Sachdeva et al., 2024). Additionally, the use of RFID Technology is proposed, which involves attaching Radio Frequency Identification (RFID) tags to products to automate inventory tracking. This technology can enhance accuracy in stock counts and reduce the time needed for inventory audits (Sundaresan et al., 2015). Lastly, an AI driven predictive analytics solution leverages artificial intelligence to predict inventory needs based on usage patterns, seasonal trends, and patient demographics, thereby optimizing stock levels by accurately forecasting demand. To evaluate these potential solutions, a feasibility analysis will be conducted using a decision-making framework that examines technical, financial, and operational feasibility. Technical feasibility assesses whether the technology needed to implement the proposed solution exists, is readily available, and can be integrated with existing hospital systems. For instance, manual inventory management has low technical feasibility as it relies on existing systems with no additional technology required. In contrast, an automated inventory management system has medium feasibility, as it may require integration with existing platforms, but proven solutions are available (Javaid et al, 2022). A cloud-based inventory management system boasts high feasibility due to the numerous options available that can integrate without significant infrastructure changes. At the same time, Radio Frequency Identification (RFID) technology presents a medium level of feasibility due to the investment

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