Implementation of IoT & AI Technology for Quality Enhancement in Real-time Pharmaceutical Storage Monitoring

Abstract

With the development of Artificial Intelligence (AI), scientists have been focusing on utilizing real-time pharmaceutical monitoring for multiple purposes. One of the main sectors benefiting from this is minimizing wastage. In this study, we introduce the ability to monitor pharmaceutical products through the integration of AI and the Internet of Things (IoT) to achieve real-time product management and waste reduction. The study introduces smart sensors that monitor the temperature and humidity of the medication in pharmacy cold storage. The system involves a decision mechanism to check for abnormalities. If regular conditions are recorded, the storage process is continued normally, and data are auto logged. However, if abnormalities are detected, the AI-assisted controller executes a bounded automatic adjustment of cooling parameters while simultaneously notifying the supervisor; all events are recorded for audit. In addition, we model the As-Is/To-Be processes using Business Process Model Notation (BPMN) and evaluate a 30-day Bizagi simulation for pharmacy cold storage. KPIs indicate substantial gains such as faster detection, alerting, corrective response, and improved auto-logging coverage. These results support the feasibility of the AI and IoT approach for improving real-time pharmaceutical monitoring and reducing potential wastage.