IoT-Enabled Smart Shelves in Pharmacies: Enhancing Stock Management Efficiency

Published Paper: PDF

DOI: https://doi.org/10.63345/ijrmp.v14.i7.5

Dr. Deepak Kumar

Santosh Medical College

Ghaziabad, Uttar Pradesh

dkak6324@gmail.com

Abstract

The rapid growth of pharmaceutical retail, coupled with increasingly stringent regulatory requirements, has accentuated the need for precise, real-time inventory visibility and control. Internet of Things (IoT)-enabled smart shelves—equipped with weight sensors, RFID readers, machine vision modules, and edge analytics—offer a transformative pathway to address stockouts, expiries, pilferage, and workflow inefficiencies in both community and hospital pharmacies. This manuscript investigates how smart shelf ecosystems can enhance stock management efficiency, reduce wastage, and strengthen patient safety. Drawing on an extensive review of extant literature and industry white papers, it elaborates an implementation framework, presents a mixed-method methodology comprising a clinical trial–style field deployment in a hospital pharmacy, and reports quantitative and qualitative results. The clinical research component evaluates metrics such as real-time stock accuracy, picking time, near-expiry detection rate, and pharmacist satisfaction over a 16-week period. Results demonstrate statistically significant reductions in stock discrepancies (−41%), time-to-replenish (−33%), and expired drug write-offs (−52%), alongside improved compliance with Good Pharmacy Practice (GPP) standards. The study concludes that IoT-enabled smart shelves, when integrated with Pharmacy Information Systems (PIS) and predictive analytics, substantially improve operational resilience and patient-centric outcomes. Implications for scalability, data governance, cybersecurity, and interoperability are discussed, with recommendations for phased adoption and continuous performance monitoring.

Keywords

IoT; smart shelves; pharmacy inventory management; RFID; real-time tracking; stockouts; expiry management; clinical trial research; hospital pharmacy; edge analytics

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