Vol. 4 No. 2 (2024): African Journal of Artificial Intelligence and Sustainable Development
Articles

IoT-enabled Smart Pharmacy Automation Systems for Medication Dispensing

Dr. Katarzyna Michalska
Associate Professor of Bioinformatics, University of Warsaw, Poland

Published 05-09-2024

Keywords

  • IoT,
  • collaboration

How to Cite

[1]
Dr. Katarzyna Michalska, “IoT-enabled Smart Pharmacy Automation Systems for Medication Dispensing”, African J. of Artificial Int. and Sust. Dev., vol. 4, no. 2, pp. 36–43, Sep. 2024, Accessed: Dec. 22, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/130

Abstract

The healthcare industry is undergoing a transformative shift towards digitalization, with a particular focus on enhancing efficiency and patient safety. In this context, the integration of Internet of Things (IoT) technology into pharmacy operations has emerged as a promising solution. This research paper explores the design and implementation of IoT-enabled smart pharmacy automation systems for medication dispensing. The aim is to streamline the dispensing process, reduce errors, and enhance overall operational efficiency in pharmacies.

The paper begins by providing an overview of the current challenges faced by traditional pharmacy dispensing systems, including manual errors, inventory management issues, and inefficient workflow. It then introduces the concept of IoT-enabled smart pharmacy automation systems, highlighting their potential to address these challenges by leveraging IoT devices such as sensors, actuators, and smart devices.

The design considerations for such systems are discussed, including the integration of IoT devices with existing pharmacy infrastructure, data security and privacy concerns, and the need for interoperability with other healthcare systems. The paper also explores the role of data analytics in optimizing medication dispensing processes, such as predicting medication demand, optimizing inventory levels, and improving patient adherence.

Several case studies and real-world implementations of IoT-enabled pharmacy automation systems are presented to illustrate their effectiveness in enhancing medication dispensing processes. These include examples of smart medication storage and retrieval systems, automated medication dispensing cabinets, and robotic dispensing systems.

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References

  1. Saeed, A., Zahoor, A., Husnain, A., & Gondal, R. M. (2024). Enhancing E-commerce furniture shopping with AR and AI-driven 3D modeling. International Journal of Science and Research Archive, 12(2), 040-046.
  2. Biswas, Anjanava, and Wrick Talukdar. "Guardrails for trust, safety, and ethical development and deployment of Large Language Models (LLM)." Journal of Science & Technology 4.6 (2023): 55-82.
  3. N. Pushadapu, “Artificial Intelligence for Standardized Data Flow in Healthcare: Techniques, Protocols, and Real-World Case Studies”, Journal of AI-Assisted Scientific Discovery, vol. 3, no. 1, pp. 435–474, Jun. 2023
  4. Chen, Jan-Jo, Ali Husnain, and Wei-Wei Cheng. "Exploring the Trade-Off Between Performance and Cost in Facial Recognition: Deep Learning Versus Traditional Computer Vision." Proceedings of SAI Intelligent Systems Conference. Cham: Springer Nature Switzerland, 2023.
  5. Alomari, Ghaith, et al. “AI-Driven Integrated Hardware and Software Solution for EEG-Based Detection of Depression and Anxiety.” International Journal for Multidisciplinary Research, vol. 6, no. 3, May 2024, pp. 1–24.
  6. Saeed, Ayesha, et al. "A Comparative Study of Cat Swarm Algorithm for Graph Coloring Problem: Convergence Analysis and Performance Evaluation." International Journal of Innovative Research in Computer Science & Technology 12.4 (2024): 1-9.
  7. Pelluru, Karthik. "Integrate security practices and compliance requirements into DevOps processes." MZ Computing Journal 2.2 (2021): 1-19.